recommend-server-client/pom.xml

@@ -10,7 +10,7 @@
     <modelVersion>4.0.0</modelVersion>
 
     <artifactId>recommend-server-client</artifactId>
-    <version>1.1.6</version>
+    <version>1.1.8</version>
 
     <dependencies>
         <dependency>

recommend-server-client/src/main/java/com/tzld/piaoquan/recommend/server/gen/recommend/Recommend.java

@@ -56,7 +56,7 @@ public final class Recommend {
       "\n2com/tzld/piaoquan/recommend/server/rec" +
       "ommend.proto\032\031google/protobuf/any.proto\032" +
       "/com/tzld/piaoquan/recommend/server/comm" +
-      "on.proto\"\334\004\n\020RecommendRequest\022\022\n\nrequest" +
+      "on.proto\"\205\005\n\020RecommendRequest\022\022\n\nrequest" +
       "_id\030\001 \001(\t\022\013\n\003mid\030\002 \001(\t\022\013\n\003uid\030\003 \001(\t\022\014\n\004s" +
       "ize\030\004 \001(\005\022\020\n\010app_type\030\005 \001(\005\022\021\n\tcity_code" +
       "\030\006 \001(\t\022\025\n\rprovince_code\030\007 \001(\t\022\023\n\013ab_exp_" +
@@ -70,25 +70,26 @@ public final class Recommend {
       "page_source\030\023 \001(\t\022\023\n\013category_id\030\024 \001(\t\022\026" +
       "\n\016hot_scene_type\030\025 \001(\003\022\021\n\tclient_ip\030\026 \001(" +
       "\t\022\024\n\014version_code\030\027 \001(\005\022\026\n\016root_source_i" +
-      "d\030\030 \001(\t\032.\n\014EventIdEntry\022\013\n\003key\030\001 \001(\t\022\r\n\005" +
-      "value\030\002 \001(\t:\0028\001\"\177\n\020MachineInfoProto\022\r\n\005b" +
-      "rand\030\001 \001(\t\022\r\n\005model\030\002 \001(\t\022\020\n\010platform\030\003 " +
-      "\001(\t\022\023\n\013sdk_version\030\004 \001(\t\022\016\n\006system\030\005 \001(\t" +
-      "\022\026\n\016wechat_version\030\006 \001(\t\"H\n\021RecommendRes" +
-      "ponse\022\027\n\006result\030\001 \001(\0132\007.Result\022\032\n\005video\030" +
-      "\002 \003(\0132\013.VideoProto\"\336\001\n\nVideoProto\022\020\n\010vid" +
-      "eo_id\030\001 \001(\003\022\021\n\trov_score\030\002 \001(\001\022\021\n\tpush_f" +
-      "rom\030\003 \001(\t\022\017\n\007ab_code\030\004 \001(\t\022\022\n\nsort_score" +
-      "\030\005 \001(\001\022\020\n\010position\030\006 \001(\005\022\021\n\tflow_pool\030\007 " +
-      "\001(\t\022\027\n\017is_in_flow_pool\030\010 \001(\005\022\014\n\004rand\030\t \001" +
-      "(\001\022\'\n\017push_from_index\030\n \003(\0132\016.PushFromIn" +
-      "dex\"1\n\rPushFromIndex\022\021\n\tpush_from\030\001 \001(\t\022" +
-      "\r\n\005index\030\002 \003(\t2\212\001\n\020RecommendService\022:\n\021H" +
-      "omepageRecommend\022\021.RecommendRequest\032\022.Re" +
-      "commendResponse\022:\n\021RelevantRecommend\022\021.R" +
-      "ecommendRequest\032\022.RecommendResponseB7\n0c" +
-      "om.tzld.piaoquan.recommend.server.gen.re" +
-      "commendP\001\210\001\001b\006proto3"
+      "d\030\030 \001(\t\022\026\n\016userShareDepth\030\031 \001(\005\022\017\n\007pageN" +
+      "um\030\032 \001(\005\032.\n\014EventIdEntry\022\013\n\003key\030\001 \001(\t\022\r\n" +
+      "\005value\030\002 \001(\t:\0028\001\"\177\n\020MachineInfoProto\022\r\n\005" +
+      "brand\030\001 \001(\t\022\r\n\005model\030\002 \001(\t\022\020\n\010platform\030\003" +
+      " \001(\t\022\023\n\013sdk_version\030\004 \001(\t\022\016\n\006system\030\005 \001(" +
+      "\t\022\026\n\016wechat_version\030\006 \001(\t\"H\n\021RecommendRe" +
+      "sponse\022\027\n\006result\030\001 \001(\0132\007.Result\022\032\n\005video" +
+      "\030\002 \003(\0132\013.VideoProto\"\336\001\n\nVideoProto\022\020\n\010vi" +
+      "deo_id\030\001 \001(\003\022\021\n\trov_score\030\002 \001(\001\022\021\n\tpush_" +
+      "from\030\003 \001(\t\022\017\n\007ab_code\030\004 \001(\t\022\022\n\nsort_scor" +
+      "e\030\005 \001(\001\022\020\n\010position\030\006 \001(\005\022\021\n\tflow_pool\030\007" +
+      " \001(\t\022\027\n\017is_in_flow_pool\030\010 \001(\005\022\014\n\004rand\030\t " +
+      "\001(\001\022\'\n\017push_from_index\030\n \003(\0132\016.PushFromI" +
+      "ndex\"1\n\rPushFromIndex\022\021\n\tpush_from\030\001 \001(\t" +
+      "\022\r\n\005index\030\002 \003(\t2\212\001\n\020RecommendService\022:\n\021" +
+      "HomepageRecommend\022\021.RecommendRequest\032\022.R" +
+      "ecommendResponse\022:\n\021RelevantRecommend\022\021." +
+      "RecommendRequest\032\022.RecommendResponseB7\n0" +
+      "com.tzld.piaoquan.recommend.server.gen.r" +
+      "ecommendP\001\210\001\001b\006proto3"
     };
     descriptor = com.google.protobuf.Descriptors.FileDescriptor
       .internalBuildGeneratedFileFrom(descriptorData,
@@ -101,7 +102,7 @@ public final class Recommend {
     internal_static_RecommendRequest_fieldAccessorTable = new
       com.google.protobuf.GeneratedMessageV3.FieldAccessorTable(
         internal_static_RecommendRequest_descriptor,
-        new java.lang.String[] { "RequestId", "Mid", "Uid", "Size", "AppType", "CityCode", "ProvinceCode", "AbExpCode", "EventId", "VersionAuditStatus", "RecommendTraceId", "VideoId", "City", "Province", "MachineInfo", "NewExpGroup", "SessionId", "SubSessionId", "PageSource", "CategoryId", "HotSceneType", "ClientIp", "VersionCode", "RootSourceId", });
+        new java.lang.String[] { "RequestId", "Mid", "Uid", "Size", "AppType", "CityCode", "ProvinceCode", "AbExpCode", "EventId", "VersionAuditStatus", "RecommendTraceId", "VideoId", "City", "Province", "MachineInfo", "NewExpGroup", "SessionId", "SubSessionId", "PageSource", "CategoryId", "HotSceneType", "ClientIp", "VersionCode", "RootSourceId", "UserShareDepth", "PageNum", });
     internal_static_RecommendRequest_EventIdEntry_descriptor =
       internal_static_RecommendRequest_descriptor.getNestedTypes().get(0);
     internal_static_RecommendRequest_EventIdEntry_fieldAccessorTable = new

recommend-server-client/src/main/java/com/tzld/piaoquan/recommend/server/gen/recommend/RecommendRequest.java

@@ -220,6 +220,16 @@ private static final long serialVersionUID = 0L;
             rootSourceId_ = s;
             break;
           }
+          case 200: {
+
+            userShareDepth_ = input.readInt32();
+            break;
+          }
+          case 208: {
+
+            pageNum_ = input.readInt32();
+            break;
+          }
           default: {
             if (!parseUnknownField(
                 input, unknownFields, extensionRegistry, tag)) {
@@ -1057,6 +1067,32 @@ private static final long serialVersionUID = 0L;
     }
   }
 
+  public static final int USERSHAREDEPTH_FIELD_NUMBER = 25;
+  private int userShareDepth_;
+  /**
+   * <pre>
+   * default -1
+   * </pre>
+   *
+   * <code>int32 userShareDepth = 25;</code>
+   * @return The userShareDepth.
+   */
+  @java.lang.Override
+  public int getUserShareDepth() {
+    return userShareDepth_;
+  }
+
+  public static final int PAGENUM_FIELD_NUMBER = 26;
+  private int pageNum_;
+  /**
+   * <code>int32 pageNum = 26;</code>
+   * @return The pageNum.
+   */
+  @java.lang.Override
+  public int getPageNum() {
+    return pageNum_;
+  }
+
   private byte memoizedIsInitialized = -1;
   @java.lang.Override
   public final boolean isInitialized() {
@@ -1146,6 +1182,12 @@ private static final long serialVersionUID = 0L;
     if (!getRootSourceIdBytes().isEmpty()) {
       com.google.protobuf.GeneratedMessageV3.writeString(output, 24, rootSourceId_);
     }
+    if (userShareDepth_ != 0) {
+      output.writeInt32(25, userShareDepth_);
+    }
+    if (pageNum_ != 0) {
+      output.writeInt32(26, pageNum_);
+    }
     unknownFields.writeTo(output);
   }
 
@@ -1246,6 +1288,14 @@ private static final long serialVersionUID = 0L;
     if (!getRootSourceIdBytes().isEmpty()) {
       size += com.google.protobuf.GeneratedMessageV3.computeStringSize(24, rootSourceId_);
     }
+    if (userShareDepth_ != 0) {
+      size += com.google.protobuf.CodedOutputStream
+        .computeInt32Size(25, userShareDepth_);
+    }
+    if (pageNum_ != 0) {
+      size += com.google.protobuf.CodedOutputStream
+        .computeInt32Size(26, pageNum_);
+    }
     size += unknownFields.getSerializedSize();
     memoizedSize = size;
     return size;
@@ -1312,6 +1362,10 @@ private static final long serialVersionUID = 0L;
         != other.getVersionCode()) return false;
     if (!getRootSourceId()
         .equals(other.getRootSourceId())) return false;
+    if (getUserShareDepth()
+        != other.getUserShareDepth()) return false;
+    if (getPageNum()
+        != other.getPageNum()) return false;
     if (!unknownFields.equals(other.unknownFields)) return false;
     return true;
   }
@@ -1379,6 +1433,10 @@ private static final long serialVersionUID = 0L;
     hash = (53 * hash) + getVersionCode();
     hash = (37 * hash) + ROOT_SOURCE_ID_FIELD_NUMBER;
     hash = (53 * hash) + getRootSourceId().hashCode();
+    hash = (37 * hash) + USERSHAREDEPTH_FIELD_NUMBER;
+    hash = (53 * hash) + getUserShareDepth();
+    hash = (37 * hash) + PAGENUM_FIELD_NUMBER;
+    hash = (53 * hash) + getPageNum();
     hash = (29 * hash) + unknownFields.hashCode();
     memoizedHashCode = hash;
     return hash;
@@ -1585,6 +1643,10 @@ private static final long serialVersionUID = 0L;
 
       rootSourceId_ = "";
 
+      userShareDepth_ = 0;
+
+      pageNum_ = 0;
+
       return this;
     }
 
@@ -1645,6 +1707,8 @@ private static final long serialVersionUID = 0L;
       result.clientIp_ = clientIp_;
       result.versionCode_ = versionCode_;
       result.rootSourceId_ = rootSourceId_;
+      result.userShareDepth_ = userShareDepth_;
+      result.pageNum_ = pageNum_;
       onBuilt();
       return result;
     }
@@ -1786,6 +1850,12 @@ private static final long serialVersionUID = 0L;
         rootSourceId_ = other.rootSourceId_;
         onChanged();
       }
+      if (other.getUserShareDepth() != 0) {
+        setUserShareDepth(other.getUserShareDepth());
+      }
+      if (other.getPageNum() != 0) {
+        setPageNum(other.getPageNum());
+      }
       this.mergeUnknownFields(other.unknownFields);
       onChanged();
       return this;
@@ -3534,6 +3604,80 @@ private static final long serialVersionUID = 0L;
       onChanged();
       return this;
     }
+
+    private int userShareDepth_ ;
+    /**
+     * <pre>
+     * default -1
+     * </pre>
+     *
+     * <code>int32 userShareDepth = 25;</code>
+     * @return The userShareDepth.
+     */
+    @java.lang.Override
+    public int getUserShareDepth() {
+      return userShareDepth_;
+    }
+    /**
+     * <pre>
+     * default -1
+     * </pre>
+     *
+     * <code>int32 userShareDepth = 25;</code>
+     * @param value The userShareDepth to set.
+     * @return This builder for chaining.
+     */
+    public Builder setUserShareDepth(int value) {
+      
+      userShareDepth_ = value;
+      onChanged();
+      return this;
+    }
+    /**
+     * <pre>
+     * default -1
+     * </pre>
+     *
+     * <code>int32 userShareDepth = 25;</code>
+     * @return This builder for chaining.
+     */
+    public Builder clearUserShareDepth() {
+      
+      userShareDepth_ = 0;
+      onChanged();
+      return this;
+    }
+
+    private int pageNum_ ;
+    /**
+     * <code>int32 pageNum = 26;</code>
+     * @return The pageNum.
+     */
+    @java.lang.Override
+    public int getPageNum() {
+      return pageNum_;
+    }
+    /**
+     * <code>int32 pageNum = 26;</code>
+     * @param value The pageNum to set.
+     * @return This builder for chaining.
+     */
+    public Builder setPageNum(int value) {
+      
+      pageNum_ = value;
+      onChanged();
+      return this;
+    }
+    /**
+     * <code>int32 pageNum = 26;</code>
+     * @return This builder for chaining.
+     */
+    public Builder clearPageNum() {
+      
+      pageNum_ = 0;
+      onChanged();
+      return this;
+    }
     @java.lang.Override
     public final Builder setUnknownFields(
         final com.google.protobuf.UnknownFieldSet unknownFields) {

recommend-server-client/src/main/java/com/tzld/piaoquan/recommend/server/gen/recommend/RecommendRequestOrBuilder.java

@@ -308,4 +308,20 @@ public interface RecommendRequestOrBuilder extends
    */
   com.google.protobuf.ByteString
       getRootSourceIdBytes();
+
+  /**
+   * <pre>
+   * default -1
+   * </pre>
+   *
+   * <code>int32 userShareDepth = 25;</code>
+   * @return The userShareDepth.
+   */
+  int getUserShareDepth();
+
+  /**
+   * <code>int32 pageNum = 26;</code>
+   * @return The pageNum.
+   */
+  int getPageNum();
 }

recommend-server-client/src/main/proto/com/tzld/piaoquan/recommend/server/recommend.proto

@@ -33,6 +33,8 @@ message RecommendRequest {
   string client_ip = 22;
   int32 version_code = 23;
   string root_source_id = 24;
+  int32 userShareDepth = 25; // default -1
+  int32 pageNum = 26;
 }
 
 message MachineInfoProto {

recommend-server-service/pom.xml

@@ -175,7 +175,7 @@
         <dependency>
             <groupId>com.tzld.piaoquan</groupId>
             <artifactId>recommend-server-client</artifactId>
-            <version>1.1.6</version>
+            <version>1.1.8</version>
         </dependency>
         <dependency>
             <groupId>com.tzld.piaoquan</groupId>

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/model/RecommendParam.java

@@ -44,5 +44,8 @@ public class RecommendParam {
     private Integer versionCode;
 
     private String rootSourceId;
+    private Integer userShareDepth;
+
+    private int pageNum;
 }
 

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/FeatureService.java

@@ -266,6 +266,7 @@ public class FeatureService {
             protos.add(genWithVidAndProvince("alg_vid_feature_feed_province_root_return_v2", vid, province));
 
             // ********************* new vid ******************
+            protos.add(genWithKeyMap("alg_recsys_feature_video_clean_stat", vid, ImmutableMap.of("vid", vid)));
             protos.add(genWithKeyMap("alg_vid_global_feature_20250212", vid, ImmutableMap.of("vid", vid)));
             protos.add(genWithKeyMap("alg_vid_recommend_exp_feature_20250212", vid, ImmutableMap.of("vid", vid)));
             protos.add(genWithKeyMap("alg_vid_recommend_flowpool_exp_feature_20250212", vid, ImmutableMap.of("vid", vid)));
@@ -386,6 +387,19 @@ public class FeatureService {
         return null;
     }
 
+    public Map<String, String> getUserInfo(String table, String id) {
+        try {
+            Feature feature = getFeatureByProto(Collections.singletonList(genWithMid(table, id)));
+            Map<String, Map<String, String>> userFeature = feature.getUserFeature();
+            if (null != userFeature) {
+                return userFeature.get(table);
+            }
+        } catch (Exception e) {
+            log.error("get user info error! value=[{}]", id, e);
+        }
+        return null;
+    }
+
     public Map<String, String> getHeadVideoInfo(String headVid) {
         try {
             if (null != headVid && !headVid.isEmpty()) {

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/RecommendService.java

@@ -12,7 +12,6 @@ import com.tzld.piaoquan.recommend.server.gen.recommend.*;
 import com.tzld.piaoquan.recommend.server.model.MachineInfo;
 import com.tzld.piaoquan.recommend.server.model.RecommendParam;
 import com.tzld.piaoquan.recommend.server.model.Video;
-import com.tzld.piaoquan.recommend.server.service.flowpool.FlowPoolConfigService;
 import com.tzld.piaoquan.recommend.server.service.flowpool.FlowPoolConstants;
 import com.tzld.piaoquan.recommend.server.service.flowpool.FlowPoolService;
 import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
@@ -28,7 +27,6 @@ import com.tzld.piaoquan.recommend.server.util.TraceUtils;
 import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.collections4.CollectionUtils;
 import org.apache.commons.collections4.MapUtils;
-import org.apache.commons.lang3.RandomUtils;
 import org.apache.commons.lang3.StringUtils;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.beans.factory.annotation.Qualifier;
@@ -353,7 +351,8 @@ public class RecommendService {
         param.setClientIp(request.getClientIp());
         param.setVersionCode(request.getVersionCode());
         param.setRootSourceId(request.getRootSourceId());
-
+        param.setUserShareDepth(request.getUserShareDepth());
+        param.setPageNum(request.getPageNum());
         return param;
     }
 
@@ -363,14 +362,14 @@ public class RecommendService {
 
         long recallTime = stopwatch.elapsed(TimeUnit.MILLISECONDS);
         timerLogMapTL.get().put("recallTime", recallTime);
-        //log.info("recallResult={}, videoRecommend recallResult cost={}", recallResult, recallTime);
+        // log.info("recallResult={}, videoRecommend recallResult cost={}", recallResult, recallTime);
         stopwatch.reset().start();
 
         RankResult rankResult = rankRouter.rank(convertToRankParam(param, recallResult));
 
         long rankTime = stopwatch.elapsed(TimeUnit.MILLISECONDS);
         timerLogMapTL.get().put("rankTime", rankTime);
-        //log.info("rankResult={}, videoRecommend rank cost={}", rankResult, rankTime);
+        // log.info("rankResult={}, videoRecommend rank cost={}", rankResult, rankTime);
 
 
         if (rankResult == null || CollectionUtils.isEmpty(rankResult.getVideos())) {
@@ -405,7 +404,7 @@ public class RecommendService {
         recallParam.setMid(param.getMid());
         recallParam.setSize(param.getSize());
         recallParam.setUid(param.getUid());
-        //风险过滤
+        // 风险过滤
         recallParam.setRiskUser(param.isRiskUser());
         recallParam.setAbExpCodes(param.getAbExpCodes());
 
@@ -417,6 +416,7 @@ public class RecommendService {
         recallParam.setHotSceneType(param.getHotSceneType());
         recallParam.setClientIp(param.getClientIp());
         recallParam.setRootSourceId(param.getRootSourceId());
+        recallParam.setUserShareDepth(param.getUserShareDepth());
 
         return recallParam;
     }
@@ -442,6 +442,8 @@ public class RecommendService {
         rankParam.setHotSceneType(param.getHotSceneType());
         rankParam.setVersionCode(param.getVersionCode());
         rankParam.setRootSourceId(param.getRootSourceId());
+        rankParam.setUserShareDepth(param.getUserShareDepth());
+        rankParam.setPageNum(param.getPageNum());
         return rankParam;
     }
 

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/RankParam.java

@@ -31,5 +31,7 @@ public class RankParam {
     private Integer categoryId;
     private Integer versionCode;
     private String rootSourceId;
+    private Integer userShareDepth;
+    private int pageNum;
 
 }

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelBasic.java

@@ -53,7 +53,7 @@ public abstract class RankStrategy4RegionMergeModelBasic extends RankService {
     @Override
     public RankResult mergeAndSort(RankParam param, List<Video> rovVideos, List<Video> flowVideos) {
 
-        //1 兜底策略，rov池子不足时，用冷启池填补。直接返回。
+        // 1 兜底策略，rov池子不足时，用冷启池填补。直接返回。
         if (CollectionUtils.isEmpty(rovVideos)) {
             if (param.getSize() < flowVideos.size()) {
                 return new RankResult(flowVideos.subList(0, param.getSize()));
@@ -62,7 +62,7 @@ public abstract class RankStrategy4RegionMergeModelBasic extends RankService {
             }
         }
 
-        //2 根据实验号解析阿波罗参数。
+        // 2 根据实验号解析阿波罗参数。
         Set<String> abExpCodes = param.getAbExpCodes();
         Map<String, Map<String, String>> rulesMap = Collections.emptyMap();
         if (CollectionUtils.isNotEmpty(abExpCodes)) {
@@ -75,23 +75,23 @@ public abstract class RankStrategy4RegionMergeModelBasic extends RankService {
         }
 
 
-        //3 标签读取
+        // 3 标签读取
         if (rulesMap != null && !rulesMap.isEmpty()) {
             RankExtractorItemTags extractorItemTags = new RankExtractorItemTags(this.redisTemplate);
             extractorItemTags.processor(rovVideos, flowVideos);
         }
-        //6 合并结果时间卡控
+        // 6 合并结果时间卡控
         if (rulesMap != null && !rulesMap.isEmpty()) {
             RankProcessorTagFilter.processor(rovVideos, flowVideos, rulesMap);
         }
 
-        //4 rov池提权功能
+        // 4 rov池提权功能
         RankProcessorBoost.boostByTag(rovVideos, rulesMap);
 
-        //5 rov池强插功能
+        // 5 rov池强插功能
         RankProcessorInsert.insertByTag(param, rovVideos, rulesMap);
 
-        //7 流量池按比例强插
+        // 7 流量池按比例强插
         List<Video> result = new ArrayList<>();
         for (int i = 0; i < param.getTopK() && i < rovVideos.size(); i++) {
             result.add(rovVideos.get(i));
@@ -126,7 +126,7 @@ public abstract class RankStrategy4RegionMergeModelBasic extends RankService {
             }
         }
 
-        //8 合并结果密度控制
+        // 8 合并结果密度控制
         Map<String, Integer> densityRules = new HashMap<>();
         if (rulesMap != null && !rulesMap.isEmpty()) {
             for (Map.Entry<String, Map<String, String>> entry : rulesMap.entrySet()) {
@@ -255,4 +255,83 @@ public abstract class RankStrategy4RegionMergeModelBasic extends RankService {
         }
     }
 
+    //------------------- 对str、ros和vor做处理，通过参数控制处理方式 -------------------
+    protected double handleStr(double originStr, double calcStrMode, RankItem item, Map<String, Double> mergeWeight) {
+        if (originStr == 0) {
+            return 0d;
+        }
+
+        double str = originStr;
+        if (calcStrMode == 1d) {
+            double strPower = mergeWeight.getOrDefault("str_power", 0d);
+            item.getScoresMap().put("strPower", strPower);
+            str = Math.pow(originStr, strPower);
+        } else if (calcStrMode == 2d) {
+            double modelStrCoefficient = mergeWeight.getOrDefault("model_str_coefficient", 8d);
+            item.getScoresMap().put("modelStrCoefficient", modelStrCoefficient);
+            str = originStr * modelStrCoefficient;
+        } else if (calcStrMode == 3d) {
+            double minVal = mergeWeight.getOrDefault("min", 0d);
+            double maxVal = mergeWeight.getOrDefault("max", 1d);
+
+            double newMinVal = mergeWeight.getOrDefault("newMin", 0.99);
+            double newMaxVal = mergeWeight.getOrDefault("newMax", 1d);
+
+            str = (originStr - minVal) / (maxVal - minVal) * (newMaxVal - newMinVal) + newMinVal;
+
+            item.getScoresMap().put("minVal", minVal);
+            item.getScoresMap().put("maxVal", maxVal);
+            item.getScoresMap().put("newMinVal", newMinVal);
+            item.getScoresMap().put("newMaxVal", newMaxVal);
+        }
+
+        return str;
+    }
+
+    protected double handleRos(double originScoreRos, double calcRosMode, RankItem item, Map<String, Double> mergeWeight) {
+        if (originScoreRos == 0) {
+            return 0;
+        }
+
+        double scoreRos = originScoreRos;
+        if (calcRosMode == 1d) {
+            double rosPower = mergeWeight.getOrDefault("le_1_ros_power", 5d);
+            if (scoreRos > 1) {
+                rosPower = mergeWeight.getOrDefault("gt_1_ros_poewr", 1.5d);
+            }
+            item.getScoresMap().put("rosPower", rosPower);
+            scoreRos = Math.pow(ExtractorUtils.inverseLog(originScoreRos), rosPower);
+        } else if (calcRosMode == 2d) {
+            double modelRosCoefficient = mergeWeight.getOrDefault("model_ros_coefficient", 8d);
+            item.getScoresMap().put("modelRosCoefficient", modelRosCoefficient);
+            scoreRos = ExtractorUtils.inverseLog(originScoreRos * modelRosCoefficient);
+        } else if (calcRosMode == 3d) {
+            double rosPower = mergeWeight.getOrDefault("ros_power", 5d);
+            item.getScoresMap().put("rosPower", rosPower);
+            scoreRos = Math.pow(ExtractorUtils.inverseLog(originScoreRos), rosPower);
+        }
+
+        return scoreRos;
+    }
+
+    protected double handleVor(double originVor, double calcVorMode, RankItem item, Map<String, Double> mergeWeight) {
+        if (originVor == 0) {
+            return 0;
+        }
+        double vor = originVor;
+        if (calcVorMode == 1d) {
+            vor = ExtractorUtils.calLog(originVor);
+        } else if (calcVorMode == 2d) {
+            double vorCoefficient = mergeWeight.getOrDefault("vor_coefficient", 1d);
+            item.getScoresMap().put("vorCoefficient", vorCoefficient);
+            vor = vorCoefficient * originVor;
+        } else if (calcVorMode == 3d) {
+            double vorPower = mergeWeight.getOrDefault("vor_power", 0d);
+            item.getScoresMap().put("vorPower", vorPower);
+            vor = Math.pow(originVor, vorPower);
+        }
+
+        return vor;
+    }
+
 }

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV562.java

@@ -1,9 +1,6 @@
 package com.tzld.piaoquan.recommend.server.service.rank.strategy;
 
 import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
-import com.google.common.collect.Maps;
-import com.google.common.collect.Sets;
-import com.google.common.reflect.TypeToken;
 import com.tzld.piaoquan.recommend.server.common.ThreadPoolFactory;
 import com.tzld.piaoquan.recommend.server.common.base.RankItem;
 import com.tzld.piaoquan.recommend.server.model.Video;
@@ -13,22 +10,16 @@ import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
 import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
 import com.tzld.piaoquan.recommend.server.service.score.ScorerUtils;
 import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
-import com.tzld.piaoquan.recommend.server.util.JSONUtils;
 import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.collections4.MapUtils;
-import org.apache.commons.lang3.StringUtils;
 import org.apache.commons.math3.util.Pair;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Service;
 
-import java.io.BufferedReader;
-import java.io.InputStream;
-import java.io.InputStreamReader;
 import java.util.*;
 import java.util.concurrent.Future;
 import java.util.concurrent.TimeUnit;
 import java.util.stream.Collectors;
-import java.util.stream.Stream;
 
 @Service
 @Slf4j
@@ -36,10 +27,6 @@ public class RankStrategy4RegionMergeModelV562 extends RankStrategy4RegionMergeM
     @ApolloJsonValue("${rank.score.merge.weightv562:}")
     private Map<String, Double> mergeWeight;
 
-    private Map<Pair<Double, Double>, Pair<Double, Double>> strPlusCalibrationCoefficientMap = Maps.newLinkedHashMap();
-
-    private static final Set<String> HOT_SCENE_TYPE_SET = Sets.newHashSet("1007", "1008");
-
     @Autowired
     private FeatureService featureService;
 
@@ -329,26 +316,64 @@ public class RankStrategy4RegionMergeModelV562 extends RankStrategy4RegionMergeM
         Map<String, String> sceneFeatureMap = new HashMap<>(0);
         List<RankItem> items = ScorerUtils.getScorerPipeline("feeds_score_config_20240807.conf").scoring(sceneFeatureMap, userFeatureMap, rankItems);
         // 5 排序公式特征
-        Map<String, Map<String, String>> vid2MapFeature = this.getVideoRedisFeature(vids, "redis:fea_hasreturn_vor:");
+        Map<String, Map<String, String>> vid2MapFeature = this.getVideoRedisFeature(vids, "redis:vid_hasreturn_vor:");
+
+        // Ros增强传播因子
+        Map<String, Map<String, String>> rosSpreadDivMap = this.getVideoRedisFeature(vids, "vid_for_spread:");
+
         List<Video> result = new ArrayList<>();
-        double strPlusPow = mergeWeight.getOrDefault("strPlusPow", 1.05);
-        for (RankItem item : items) {
 
+        double calcVorMode = mergeWeight.getOrDefault("calcVorMode", 3d);
+        double calcRosMode = mergeWeight.getOrDefault("calcRosMode", 0d);
+        double calcStrMode = mergeWeight.getOrDefault("calcStrMode", 3d);
+
+        double rosAdd = mergeWeight.getOrDefault("ros_add", 0.1d);
+        double ros2Multi = mergeWeight.getOrDefault("ros2_multi", 1d);
+        double vorAdd = mergeWeight.getOrDefault("vor_add", 0d);
+
+        double rosSpreadDivisorIndex = mergeWeight.getOrDefault("rosSpreadDivisorIndex", 4d);
+        String spreadDivisorKey = this.indexCoverKey(rosSpreadDivisorIndex);
+        log.info("562 spreadDivisorKey is: {}", spreadDivisorKey);
+
+        for (RankItem item : items) {
+            double score;
             double fmRovOrigin = item.getScoreRov();
             item.getScoresMap().put("fmRovOrigin", fmRovOrigin);
-            double fmRov = restoreScore(fmRovOrigin);
-            item.getScoresMap().put("fmRovRestore", fmRov);
-            fmRov = Math.pow(fmRov, strPlusPow);
-            item.getScoresMap().put("fmRov", fmRov);
-            item.getScoresMap().put("strPlusPow", strPlusPow);
-
-            double hasReturnRovScore = this.calcHasReturnRovScore(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()), param.getHotSceneType().toString(), item);
-            hasReturnRovScore = Math.pow(hasReturnRovScore, 1.1);
-            item.getScoresMap().put("hasReturnRovScore", hasReturnRovScore);
-            double vor = this.calcVorScore(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()));
+            double str = restoreScore(fmRovOrigin);
+            item.getScoresMap().put("originStr", str);
+            str = this.handleStr(str, calcStrMode, item, mergeWeight);
+            item.getScoresMap().put("xgbRovNegRate", 0.9d);
+            item.getScoresMap().put("fmRov", str);
+            item.getScoresMap().put("str", str);
+            item.getScoresMap().put("calcStrMode", calcStrMode);
+
+            double originRos = Double.parseDouble(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()).getOrDefault("rov", "0"));
+            double ros = this.handleRos(originRos, calcRosMode, item, mergeWeight);
+            item.getScoresMap().put("hasReturnRovScore", ros);
+            item.getScoresMap().put("ros", ros);
+            item.getScoresMap().put("originRos", originRos);
+            item.getScoresMap().put("calcRosMode", calcRosMode);
+
+            String spreadDivStr = rosSpreadDivMap.getOrDefault(String.valueOf(item.getVideoId()), new HashMap<>()).getOrDefault(spreadDivisorKey, "0");
+            double rosSpreadDiv = Double.parseDouble(spreadDivStr);
+            item.getScoresMap().put("rosSpreadDiv", rosSpreadDiv);
+
+            double originVor = Double.parseDouble(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()).getOrDefault("vor", "0"));
+            double vor = this.handleVor(originVor, calcVorMode, item, mergeWeight);
+            item.getScoresMap().put("originVor", originVor);
             item.getScoresMap().put("vor", vor);
-            double score = fmRov * (0.1 + hasReturnRovScore) * (0.1 + vor);
+            item.getScoresMap().put("calcVorMode", calcVorMode);
+
+
+            item.getScoresMap().put("rosAdd", rosAdd);
+            item.getScoresMap().put("vorAdd", vorAdd);
+            item.getScoresMap().put("ros2Multi", ros2Multi);
+            item.getScoresMap().put("rosSpreadDivisorIndex", rosSpreadDivisorIndex);
+            score = str * (rosAdd + ros + ros2Multi * rosSpreadDiv) * (vorAdd + vor);
+
             Video video = item.getVideo();
+            video.setScoreStr(str);
+            video.setScoreRos(rosAdd + ros + ros2Multi * rosSpreadDiv);
             video.setScore(score);
             video.setSortScore(score);
             video.setScoresMap(item.getScoresMap());
@@ -365,109 +390,16 @@ public class RankStrategy4RegionMergeModelV562 extends RankStrategy4RegionMergeM
         return result;
     }
 
-    private double calcHasReturnRovScore(Map<String, String> feature, String hotSceneType, RankItem item) {
-
-        try {
-
-            if (!HOT_SCENE_TYPE_SET.contains(hotSceneType)) {
-                hotSceneType = "other";
-            }
-
-            Map<String, String> sumJson = JSONUtils.fromJson(feature.getOrDefault("sum", "{}"), new TypeToken<Map<String, String>>() {
-            }, new HashMap<>());
-            Map<String, String> hotSceneJson = JSONUtils.fromJson(feature.getOrDefault(hotSceneType, "{}"), new TypeToken<Map<String, String>>() {
-            }, new HashMap<>());
-
-            String sumHasReturn = sumJson.getOrDefault("hasreturn", "0");
-            String hotSceneHasReturn = hotSceneJson.getOrDefault("hasreturn", sumHasReturn);
-
-            item.getScoresMap().put("hotSceneTypeHasReturn", Double.parseDouble(hotSceneHasReturn));
-            item.getScoresMap().put("sumHasReturn", Double.parseDouble(sumHasReturn));
-
-            return Stream.of(hotSceneHasReturn, sumHasReturn)
-                    .mapToDouble(Double::parseDouble)
-                    .average().orElse(0.0);
-
-        } catch (Exception e) {
-            log.error("[562 exp] calc has return rov score error: {}, {}", feature, hotSceneType, e);
-            return 0;
-        }
-    }
-
-    private double calcVorScore(Map<String, String> feature) {
-        try {
-            Map<String, String> sumJson = JSONUtils.fromJson(feature.getOrDefault("sum", "{}"), new TypeToken<Map<String, String>>() {
-            }, new HashMap<>());
-            return Double.parseDouble(sumJson.getOrDefault("vor", "0"));
-        } catch (Exception e) {
-            log.error("[562 exp] calc vor score error: {}", feature, e);
-            return 0;
-        }
-    }
-
-    private double fmRovRestoreAndCalibration(RankItem item) {
-        double fmRovOrigin = item.getScoreRov();
-        // fmRov采样恢复
-        double fmRov = restoreScore(fmRovOrigin);
-        item.getScoresMap().put("fmRovRestore", fmRov);
-        if (fmRov < 0) {
-            fmRov = 0;
-        }
-        if (fmRov > 1) {
-            fmRov = 1;
-        }
-        try {
-            readCalibrationFile();
-
-            for (Map.Entry<Pair<Double, Double>, Pair<Double, Double>> entry : strPlusCalibrationCoefficientMap.entrySet()) {
-                Pair<Double, Double> region = entry.getKey();
-                if (region.getFirst() <= fmRov && fmRov < region.getSecond()) {
-                    item.getScoresMap().put("fmRovCalibrationCoefficient", entry.getValue().getSecond());
-                    return fmRov * entry.getValue().getSecond();
-                }
-            }
-        } catch (Exception e) {
-            log.info("[562 exp] str plus calibration error: {}", fmRov, e);
-        }
-        return fmRov;
-    }
-
-    private void readCalibrationFile() {
-        if (MapUtils.isNotEmpty(strPlusCalibrationCoefficientMap)) {
-            return;
-        }
-        synchronized (this) {
-            if (MapUtils.isNotEmpty(strPlusCalibrationCoefficientMap)) {
-                return;
-            }
-            InputStream resourceStream = RankStrategy4RegionMergeModelV562.class.getClassLoader().getResourceAsStream("562_calibration_coefficient.txt");
-            if (Objects.isNull(resourceStream)) {
-                log.error("[562 exp] read calibration file error: calibration not found");
-                return;
-            }
-            try (BufferedReader reader = new BufferedReader(new InputStreamReader(resourceStream))) {
-                String line;
-                while ((line = reader.readLine()) != null) {
-                    line = line.replace(" ", "").replaceAll("\n", "");
-                    if (StringUtils.isEmpty(line)) {
-                        continue;
-                    }
-
-                    String[] split = line.split(",");
-                    if (split.length != 4) {
-                        continue;
-                    }
-                    Double rangeBegin = Double.parseDouble(split[0]);
-                    Double rangeEnd = Double.parseDouble(split[1]);
-                    Double originCoefficient = Double.parseDouble(split[2]);
-                    Double smoothlyCoefficient = Double.parseDouble(split[3]);
-                    strPlusCalibrationCoefficientMap.put(new Pair<>(rangeBegin, rangeEnd), new Pair<>(originCoefficient, smoothlyCoefficient));
-                }
-            } catch (Exception e) {
-                log.error("[562 exp] read calibration file error: ", e);
-            }
-
-
+    private String indexCoverKey(double index) {
+        switch ((int) index) {
+            case 1:
+                return "head_video_rov1";
+            case 3:
+                return "head_video_recommend_rovn";
+            case 4:
+                return "head_video_recommend_fission_rate";
+            default:
+                return "recommend_123_depth_fission_rate";
         }
     }
 

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV564.java

@@ -4,13 +4,13 @@ import com.alibaba.fastjson.JSON;
 import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
 import com.tzld.piaoquan.recommend.server.common.ThreadPoolFactory;
 import com.tzld.piaoquan.recommend.server.common.base.RankItem;
+import com.tzld.piaoquan.recommend.server.model.MachineInfo;
 import com.tzld.piaoquan.recommend.server.model.Video;
 import com.tzld.piaoquan.recommend.server.service.FeatureService;
 import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
 import com.tzld.piaoquan.recommend.server.service.rank.bo.UserSRBO;
 import com.tzld.piaoquan.recommend.server.service.rank.bo.UserShareReturnProfile;
-import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
-import com.tzld.piaoquan.recommend.server.service.rank.tansform.NORFeature;
+import com.tzld.piaoquan.recommend.server.service.rank.tansform.FeatureV6;
 import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
 import com.tzld.piaoquan.recommend.server.service.score.ScorerUtils;
 import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
@@ -18,7 +18,6 @@ import com.tzld.piaoquan.recommend.server.util.FeatureBucketUtils;
 import com.tzld.piaoquan.recommend.server.util.JSONUtils;
 import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.collections4.MapUtils;
-import org.apache.commons.math3.util.Pair;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Service;
 
@@ -84,16 +83,27 @@ public class RankStrategy4RegionMergeModelV564 extends RankStrategy4RegionMergeM
         sceneCFRosn = sceneCFRosn.subList(0, Math.min(mergeWeight.getOrDefault("sceneCFRosn", 5.0).intValue(), sceneCFRosn.size()));
         rovRecallRank.addAll(sceneCFRosn);
         setVideo.addAll(sceneCFRosn.stream().map(Video::getVideoId).collect(Collectors.toSet()));
+        // -------------------cate1------------------
+        int cate1RecallN = mergeWeight.getOrDefault("cate1RecallN", 5.0).intValue();
+        addRecall(param, cate1RecallN, UserCate1RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        // -------------------cate2------------------
+        int cate2RecallN = mergeWeight.getOrDefault("cate2RecallN", 5.0).intValue();
+        addRecall(param, cate2RecallN, UserCate2RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        // -------------------head province cate1------------------
+        int headCate1RecallN = mergeWeight.getOrDefault("headCate1RecallN", 5.0).intValue();
+        addRecall(param, headCate1RecallN, HeadProvinceCate1RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        // -------------------head province cate2------------------
+        int headCate2RecallN = mergeWeight.getOrDefault("headCate2RecallN", 5.0).intValue();
+        addRecall(param, headCate2RecallN, HeadProvinceCate2RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
 
         //-------------------排-------------------
         //-------------------序-------------------
         //-------------------逻-------------------
         //-------------------辑-------------------
 
-        // 1 批量获取特征  省份参数要对齐  headvid  要传递过来！
-        List<String> vids = CommonCollectionUtils.toListDistinct(rovRecallRank, v -> String.valueOf(v.getVideoId()));
-
+        // 1. 批量获取特征  省份参数要对齐  headvid  要传递过来！
         // k1:视频、k2:表、k3:特征、v:特征值
+        List<String> vids = CommonCollectionUtils.toListDistinct(rovRecallRank, v -> String.valueOf(v.getVideoId()));
         String headVid = String.valueOf(param.getHeadVid());
         Map<String, Map<String, Map<String, String>>> videoBaseInfoMap = featureService.getVideoBaseInfo(headVid, vids);
         FeatureService.Feature feature = featureService.getFeatureV3(param, videoBaseInfoMap, vids);
@@ -101,247 +111,33 @@ public class RankStrategy4RegionMergeModelV564 extends RankStrategy4RegionMergeM
         Map<String, Map<String, Map<String, String>>> featureOriginVideo = feature.getVideoFeature();
         Map<String, String> headVideoInfo = videoBaseInfoMap.getOrDefault(headVid, new HashMap<>()).getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
 
-        // 用户信息预处理
-        Map<String, Map<String, String[]>> newC7Map = NORFeature.parseUCFScore(featureOriginUser.getOrDefault("alg_mid_feature_sharecf", new HashMap<>()));
-        Map<String, Map<String, String[]>> newC8Map = NORFeature.parseUCFScore(featureOriginUser.getOrDefault("alg_mid_feature_returncf", new HashMap<>()));
+        // 2. 用户信息预处理
+        Map<String, Map<String, String[]>> newC7Map = FeatureV6.parseUCFScore(featureOriginUser.getOrDefault("alg_mid_feature_sharecf", new HashMap<>()));
+        Map<String, Map<String, String[]>> newC8Map = FeatureV6.parseUCFScore(featureOriginUser.getOrDefault("alg_mid_feature_returncf", new HashMap<>()));
         UserShareReturnProfile userProfile = parseUserProfile(featureOriginUser);
         Map<String, Map<String, String>> userBehaviorVideoMap = getUserBehaviorVideoMap(userProfile);
 
-        // 2 特征处理
-        Map<String, Double> userFeatureMapDouble = new HashMap<>();
-        String mid = param.getMid();
-        Map<String, String> c1 = featureOriginUser.getOrDefault("alg_mid_feature_play", new HashMap<>());
-        Map<String, String> c2 = featureOriginUser.getOrDefault("alg_mid_feature_share_and_return", new HashMap<>());
-        Map<String, String> c3 = featureOriginUser.getOrDefault("alg_mid_feature_play_tags", new HashMap<>());
-        Map<String, String> c4 = featureOriginUser.getOrDefault("alg_mid_feature_return_tags", new HashMap<>());
-        Map<String, String> c5 = featureOriginUser.getOrDefault("alg_mid_feature_share_tags", new HashMap<>());
-        Map<String, String> c6 = featureOriginUser.getOrDefault("alg_mid_feature_feed_exp_share_tags_v2", new HashMap<>());
-        Map<String, String> c7 = featureOriginUser.getOrDefault("alg_mid_feature_feed_exp_return_tags_v2", new HashMap<>());
-        Map<String, String> c8 = featureOriginUser.getOrDefault("alg_mid_feature_sharecf", new HashMap<>());
-        Map<String, String> c9 = featureOriginUser.getOrDefault("alg_mid_feature_returncf", new HashMap<>());
-
-        if (!c1.isEmpty()) {
-            userFeatureMapDouble.put("playcnt_6h", Double.parseDouble(c1.getOrDefault("playcnt_6h", "0")));
-            userFeatureMapDouble.put("playcnt_1d", Double.parseDouble(c1.getOrDefault("playcnt_1d", "0")));
-            userFeatureMapDouble.put("playcnt_3d", Double.parseDouble(c1.getOrDefault("playcnt_3d", "0")));
-            userFeatureMapDouble.put("playcnt_7d", Double.parseDouble(c1.getOrDefault("playcnt_7d", "0")));
-        }
-        if (!c2.isEmpty()) {
-            userFeatureMapDouble.put("share_pv_12h", Double.parseDouble(c2.getOrDefault("share_pv_12h", "0")));
-            userFeatureMapDouble.put("share_pv_1d", Double.parseDouble(c2.getOrDefault("share_pv_1d", "0")));
-            userFeatureMapDouble.put("share_pv_3d", Double.parseDouble(c2.getOrDefault("share_pv_3d", "0")));
-            userFeatureMapDouble.put("share_pv_7d", Double.parseDouble(c2.getOrDefault("share_pv_7d", "0")));
-            userFeatureMapDouble.put("return_uv_12h", Double.parseDouble(c2.getOrDefault("return_uv_12h", "0")));
-            userFeatureMapDouble.put("return_uv_1d", Double.parseDouble(c2.getOrDefault("return_uv_1d", "0")));
-            userFeatureMapDouble.put("return_uv_3d", Double.parseDouble(c2.getOrDefault("return_uv_3d", "0")));
-            userFeatureMapDouble.put("return_uv_7d", Double.parseDouble(c2.getOrDefault("return_uv_7d", "0")));
-        }
-
-        Map<String, String> c34567Map = new HashMap<>(15);
-        List<Tuple2> tmpList0 = Arrays.asList(
-                new Tuple2(c3, "c3_feature"),
-                new Tuple2(c4, "c4_feature"),
-                new Tuple2(c5, "c5_feature"),
-                new Tuple2(c6, "c6_feature"),
-                new Tuple2(c7, "c7_feature")
-        );
-        for (Tuple2 tuple2 : tmpList0) {
-            for (String key_time : Arrays.asList("tags_1d", "tags_3d", "tags_7d")) {
-                String tags = tuple2.first.getOrDefault(key_time, "");
-                if (!tags.isEmpty()) {
-                    c34567Map.put(tuple2.name + "_" + key_time, tags);
-                }
-            }
-        }
-
-        Map<String, Map<String, String[]>> c89Map = new HashMap<>(4);
-        List<Tuple2> tmpList1 = Arrays.asList(
-                new Tuple2(c8, "c8_feature"),
-                new Tuple2(c9, "c9_feature")
-        );
-        for (Tuple2 tuple2 : tmpList1) {
-            for (String key_action : Arrays.asList("share", "return")) {
-                String cfListStr = tuple2.first.getOrDefault(key_action, "");
-                if (!cfListStr.isEmpty()) {
-                    Map<String, String[]> cfMap = new HashMap<>();
-                    String[] entries = cfListStr.split(",");
-                    for (String entry : entries) {
-                        String[] rList = entry.split(":");
-                        if (rList.length >= 4) { // 确保分割后有四个元素
-                            String key = rList[0];
-                            String value1 = rList[1];
-                            String value2 = rList[2];
-                            String value3 = rList[3];
-                            String[] strs = {value1, value2, value3};
-                            cfMap.put(key, strs);
-                        }
-                    }
-                    c89Map.put(tuple2.name + "_" + key_action, cfMap);
-                }
-            }
-        }
-
-
+        // 3. 特征处理
         List<RankItem> rankItems = CommonCollectionUtils.toList(rovRecallRank, RankItem::new);
-        for (RankItem item : rankItems) {
-            Map<String, Double> featureMap = new HashMap<>();
-            String vid = item.getVideoId() + "";
-            Map<String, String> b1 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_all_exp_v2", new HashMap<>());
-            Map<String, String> b2 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_all_share", new HashMap<>());
-            Map<String, String> b3 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_all_return", new HashMap<>());
-            Map<String, String> b6 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_exp2share_v2", new HashMap<>());
-            Map<String, String> b7 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_share2return", new HashMap<>());
-
-            Map<String, String> b8 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_noflow_exp_v2", new HashMap<>());
-            Map<String, String> b9 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_noflow_root_share_v2", new HashMap<>());
-            Map<String, String> b10 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_noflow_root_return_v2", new HashMap<>());
-            Map<String, String> b11 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_flow_exp_v2", new HashMap<>());
-            Map<String, String> b12 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_flow_root_share_v2", new HashMap<>());
-            Map<String, String> b13 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_flow_root_return_v2", new HashMap<>());
-            Map<String, String> b17 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_province_exp_v2", new HashMap<>());
-            Map<String, String> b18 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_province_root_share_v2", new HashMap<>());
-            Map<String, String> b19 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_province_root_return_v2", new HashMap<>());
-
-            List<Tuple4> originData = Arrays.asList(
-                    new Tuple4(b1, b2, b3, "b123"),
-                    new Tuple4(b1, b6, b7, "b167"),
-                    new Tuple4(b8, b9, b10, "b8910"),
-                    new Tuple4(b11, b12, b13, "b111213"),
-                    new Tuple4(b17, b18, b19, "b171819")
-            );
-
-            for (Tuple4 tuple4 : originData) {
-                for (String prefix2 : Arrays.asList("1h", "2h", "3h", "4h", "12h", "1d", "3d", "7d")) {
-                    double exp = tuple4.first.isEmpty() ? 0 : Double.parseDouble(tuple4.first.getOrDefault("exp_pv_" + prefix2, "0.0"));
-                    double share = tuple4.second.isEmpty() ? 0 : Double.parseDouble(tuple4.second.getOrDefault("share_pv_" + prefix2, "0.0"));
-                    double returns = tuple4.third.isEmpty() ? 0 : Double.parseDouble(tuple4.third.getOrDefault("return_uv_" + prefix2, "0.0"));
-
-                    double f1 = ExtractorUtils.calDiv(share, exp);
-                    double f2 = ExtractorUtils.calLog(share);
-                    double f3 = ExtractorUtils.calDiv(returns, exp);
-                    double f4 = ExtractorUtils.calLog(returns);
-                    double f5 = f3 * f4;
-
-                    String key1 = tuple4.name + "_" + prefix2 + "_" + "STR";
-                    String key2 = tuple4.name + "_" + prefix2 + "_" + "log(share)";
-                    String key3 = tuple4.name + "_" + prefix2 + "_" + "ROV";
-                    String key4 = tuple4.name + "_" + prefix2 + "_" + "log(return)";
-                    String key5 = tuple4.name + "_" + prefix2 + "_" + "ROV*log(return)";
-
-                    featureMap.put(key1, f1);
-                    featureMap.put(key2, f2);
-                    featureMap.put(key3, f3);
-                    featureMap.put(key4, f4);
-                    featureMap.put(key5, f5);
-                }
-            }
-
-            Map<String, String> videoInfo = videoBaseInfoMap.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
-            featureMap.put("total_time", Double.parseDouble(videoInfo.getOrDefault("total_time", "0")));
-            featureMap.put("bit_rate", Double.parseDouble(videoInfo.getOrDefault("bit_rate", "0")));
-
-            String title = videoInfo.getOrDefault("title", "");
-            if (!title.isEmpty()) {
-                List<Future<Pair<String, Double[]>>> futures = new ArrayList<>();
-                for (String name : Arrays.asList("c3_feature", "c4_feature", "c5_feature", "c6_feature", "c7_feature")) {
-                    for (String key_time : Arrays.asList("tags_1d", "tags_3d", "tags_7d")) {
-                        String key = name + "_" + key_time;
-                        String tags = c34567Map.getOrDefault(key, "");
-                        if (!tags.isEmpty()) {
-                            Future<Pair<String, Double[]>> future = ThreadPoolFactory.defaultPool().submit(() -> {
-                                Double[] doubles = ExtractorUtils.funcC34567ForTagsNew(tags, title);
-                                return Pair.create(key, doubles);
-                            });
-                            futures.add(future);
-                        }
-                    }
-                }
-                try {
-                    for (Future<Pair<String, Double[]>> future : futures) {
-                        Pair<String, Double[]> pair = future.get(1000, TimeUnit.MILLISECONDS);
-                        featureMap.put(pair.getFirst() + "_matchnum", pair.getSecond()[0]);
-                        featureMap.put(pair.getFirst() + "_maxscore", pair.getSecond()[1]);
-                        featureMap.put(pair.getFirst() + "_avgscore", pair.getSecond()[2]);
-                    }
-                } catch (Exception e) {
-                    log.error("concurrent similarity error", e);
-                }
-            }
-
-            if (!vid.isEmpty()) {
-                for (String key_feature : Arrays.asList("c8_feature", "c9_feature")) {
-                    for (String key_action : Arrays.asList("share", "return")) {
-                        Map<String, String[]> cfMap = c89Map.getOrDefault(key_feature + "_" + key_action, new HashMap<>());
-                        if (cfMap.containsKey(vid)) {
-                            String[] scores = cfMap.get(vid);
-                            Double score1 = Double.parseDouble(scores[0]);
-                            Double score2 = Double.parseDouble(scores[1]);
-                            Double score3 = Double.parseDouble(scores[2]) <= 0 ? 0D : 1.0 / Double.parseDouble(scores[2]);
-                            featureMap.put(key_feature + "_" + key_action + "_score", score1);
-                            featureMap.put(key_feature + "_" + key_action + "_num", score2);
-                            featureMap.put(key_feature + "_" + key_action + "_rank", score3);
-                        }
-                    }
-                }
-            }
-            Map<String, String> d1 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_recsys_feature_cf_i2i_new_v2", new HashMap<>());
-            if (!d1.isEmpty()) {
-                featureMap.put("d1_exp", Double.parseDouble(d1.getOrDefault("exp", "0")));
-                featureMap.put("d1_return_n", Double.parseDouble(d1.getOrDefault("return_n", "0")));
-                featureMap.put("d1_rovn", Double.parseDouble(d1.getOrDefault("rovn", "0")));
-            }
-            item.featureMapDouble = featureMap;
-        }
-
-        // get nor feature
-        Map<String, String> norUserFeatureMap = getNorUserFeature(currentMs, headVideoInfo, userProfile, featureOriginUser);
-        batchGetNorVideoFeature(currentMs, userProfile, headVideoInfo, videoBaseInfoMap,
+        Map<String, String> userFeatureMap = getUserFeature(currentMs, param, headVideoInfo, userProfile, featureOriginUser);
+        batchGetVideoFeature(currentMs, userProfile, headVideoInfo, videoBaseInfoMap,
                 newC7Map, newC8Map, featureOriginUser, userBehaviorVideoMap, featureOriginVideo, rankItems);
 
-        // 3 连续值特征分桶
-        readBucketFile();
-        Map<String, String> userFeatureMap = new HashMap<>(userFeatureMapDouble.size());
-        for (Map.Entry<String, Double> entry : userFeatureMapDouble.entrySet()) {
-            String name = entry.getKey();
-            Double score = entry.getValue();
-            // 注意：0值、不在分桶文件中的特征，会被过滤掉。
-            if (score > 1E-8 && this.bucketsLen.containsKey(name) && this.bucketsMap.containsKey(name)) {
-                Double bucketNum = this.bucketsLen.get(name);
-                double[] buckets = this.bucketsMap.get(name);
-                Double scoreNew = 1.0 / bucketNum * (ExtractorUtils.findInsertPosition(buckets, score) + 1.0);
-                userFeatureMap.put(name, String.valueOf(scoreNew));
-            }
-        }
-        for (RankItem item : rankItems) {
-            Map<String, String> featureMap = new HashMap<>();
-            Map<String, Double> featureMapDouble = item.featureMapDouble;
+        // 4. 排序模型计算
+        Map<String, String> sceneFeatureMap = new HashMap<>(0);
+        List<RankItem> items = ScorerUtils.getScorerPipeline("feeds_score_config_fm_xgb_20250317.conf").scoring(sceneFeatureMap, userFeatureMap, userFeatureMap, rankItems);
 
-            for (Map.Entry<String, Double> entry : featureMapDouble.entrySet()) {
-                String name = entry.getKey();
-                Double score = entry.getValue();
-                // 注意：0值、不在分桶文件中的特征，会被过滤掉。
-                if (score > 1E-8 && this.bucketsLen.containsKey(name) && this.bucketsMap.containsKey(name)) {
-                    Double bucketNum = this.bucketsLen.get(name);
-                    double[] buckets = this.bucketsMap.get(name);
-                    Double scoreNew = 1.0 / bucketNum * (ExtractorUtils.findInsertPosition(buckets, score) + 1.0);
-                    featureMap.put(name, String.valueOf(scoreNew));
-                }
-            }
-            item.featureMap = featureMap;
-        }
-        // 4 排序模型计算
+        // 5. 排序公式特征
+        double xgbRovNegRate = mergeWeight.getOrDefault("xgbRovNegRate", 0.059);
         double xgbNorPowerWeight = mergeWeight.getOrDefault("xgbNorPowerWeight", 1.22);
         double xgbNorPowerExp = mergeWeight.getOrDefault("xgbNorPowerExp", 1.24);
-        Map<String, String> sceneFeatureMap = new HashMap<>(0);
-        List<RankItem> items = ScorerUtils.getScorerPipeline("feeds_score_config_fm_xgb_20250221.conf").scoring(sceneFeatureMap, userFeatureMap, norUserFeatureMap, rankItems);
-        // 5 排序公式特征
         Map<String, Map<String, String>> vid2MapFeature = this.getVideoRedisFeature(vids, "redis:vid_hasreturn_vor:");
         List<Video> result = new ArrayList<>();
         for (RankItem item : items) {
             double score;
             double fmRovOrigin = item.getScoreRov();
             item.getScoresMap().put("fmRovOrigin", fmRovOrigin);
-            double fmRov = restoreScore(fmRovOrigin);
+            double fmRov = restoreScore(fmRovOrigin, xgbRovNegRate);
             item.getScoresMap().put("fmRov", fmRov);
             double hasReturnRovScore = Double.parseDouble(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()).getOrDefault("rov", "0"));
             item.getScoresMap().put("hasReturnRovScore", hasReturnRovScore);
@@ -420,66 +216,70 @@ public class RankStrategy4RegionMergeModelV564 extends RankStrategy4RegionMergeM
         return historyVideoMap;
     }
 
-    private Map<String, String> getNorUserFeature(long currentMs, Map<String, String> headInfo, UserShareReturnProfile userProfile, Map<String, Map<String, String>> userOriginInfo) {
+    private Map<String, String> getUserFeature(long currentMs, RankParam param, Map<String, String> headInfo, UserShareReturnProfile userProfile, Map<String, Map<String, String>> userOriginInfo) {
         Map<String, Double> featMap = new HashMap<>();
         // context feature
-        NORFeature.getContextFeature(currentMs, featMap);
+        String appType = String.valueOf(param.getAppType());
+        String hotSceneType = String.valueOf(param.getHotSceneType());
+        FeatureV6.getContextFeature(currentMs, appType, hotSceneType, featMap);
 
         // head video feature
-        NORFeature.getVideoBaseFeature("h", currentMs, headInfo, featMap);
+        FeatureV6.getVideoBaseFeature("h", currentMs, headInfo, featMap);
 
         // user feature
-        NORFeature.getUserFeature(userOriginInfo, featMap);
-        NORFeature.getUserProfileFeature(userProfile, featMap);
+        Map<String, String> baseInfo = getUserBaseInfo(param);
+        FeatureV6.getUserFeature(userOriginInfo, featMap);
+        FeatureV6.getUserProfileFeature(userProfile, baseInfo, featMap);
 
         return FeatureBucketUtils.noBucketFeature(featMap);
     }
 
-    private Map<String, String> getNorVideoFeature(long currentMs, String vid,
-                                                   UserShareReturnProfile userProfile,
-                                                   Map<String, String> headInfo, Map<String, String> rankInfo,
-                                                   Map<String, Map<String, String[]>> c7Map,
-                                                   Map<String, Map<String, String[]>> c8Map,
-                                                   Map<String, Map<String, String>> userOriginInfo,
-                                                   Map<String, Map<String, String>> historyVideoMap,
-                                                   Map<String, Map<String, Map<String, String>>> videoOriginInfo) {
+    private Map<String, String> getVideoFeature(long currentMs, String vid,
+                                                UserShareReturnProfile userProfile,
+                                                Map<String, String> headInfo, Map<String, String> rankInfo,
+                                                Map<String, Map<String, String[]>> c7Map,
+                                                Map<String, Map<String, String[]>> c8Map,
+                                                Map<String, Map<String, String>> userOriginInfo,
+                                                Map<String, Map<String, String>> historyVideoMap,
+                                                Map<String, Map<String, Map<String, String>>> videoOriginInfo) {
         Map<String, Double> featMap = new HashMap<>();
         // user & video feature
-        NORFeature.getUserTagsCrossVideoFeature("c5", rankInfo, userOriginInfo.get("alg_mid_feature_return_tags"), featMap);
-        NORFeature.getUserTagsCrossVideoFeature("c6", rankInfo, userOriginInfo.get("alg_mid_feature_share_tags"), featMap);
-        NORFeature.getUserCFFeature("c7", vid, c7Map, featMap);
-        NORFeature.getUserCFFeature("c8", vid, c8Map, featMap);
+        FeatureV6.getUserTagsCrossVideoFeature("c5", rankInfo, userOriginInfo.get("alg_mid_feature_return_tags"), featMap);
+        FeatureV6.getUserTagsCrossVideoFeature("c6", rankInfo, userOriginInfo.get("alg_mid_feature_share_tags"), featMap);
+        FeatureV6.getUserCFFeature("c7", vid, c7Map, featMap);
+        FeatureV6.getUserCFFeature("c8", vid, c8Map, featMap);
 
         // rank video feature
-        NORFeature.getVideoBaseFeature("r", currentMs, rankInfo, featMap);
-        NORFeature.getVideoFeature(vid, videoOriginInfo, featMap);
+        FeatureV6.getVideoBaseFeature("r", currentMs, rankInfo, featMap);
+        FeatureV6.getVideoFeature(vid, videoOriginInfo, featMap);
 
         // head&rank cross feature
-        NORFeature.getHeadRankVideoCrossFeature(headInfo, rankInfo, featMap);
+        FeatureV6.getHeadRankVideoCrossFeature(headInfo, rankInfo, featMap);
 
         // user profile & rank cross
-        NORFeature.getProfileVideoCrossFeature(currentMs, userProfile, rankInfo, historyVideoMap, featMap);
+        FeatureV6.getProfileVideoCrossFeature(currentMs, userProfile, rankInfo, historyVideoMap, featMap);
 
         return FeatureBucketUtils.noBucketFeature(featMap);
     }
 
-    private void batchGetNorVideoFeature(long currentMs,
-                                         UserShareReturnProfile userProfile,
-                                         Map<String, String> headInfo,
-                                         Map<String, Map<String, Map<String, String>>> videoBaseInfoMap,
-                                         Map<String, Map<String, String[]>> c7Map,
-                                         Map<String, Map<String, String[]>> c8Map,
-                                         Map<String, Map<String, String>> userOriginInfo,
-                                         Map<String, Map<String, String>> historyVideoMap,
-                                         Map<String, Map<String, Map<String, String>>> videoOriginInfo,
-                                         List<RankItem> rankItems) {
+    private void batchGetVideoFeature(long currentMs,
+                                      UserShareReturnProfile userProfile,
+                                      Map<String, String> headInfo,
+                                      Map<String, Map<String, Map<String, String>>> videoBaseInfoMap,
+                                      Map<String, Map<String, String[]>> c7Map,
+                                      Map<String, Map<String, String[]>> c8Map,
+                                      Map<String, Map<String, String>> userOriginInfo,
+                                      Map<String, Map<String, String>> historyVideoMap,
+                                      Map<String, Map<String, Map<String, String>>> videoOriginInfo,
+                                      List<RankItem> rankItems) {
         if (null != rankItems && !rankItems.isEmpty()) {
             List<Future<Integer>> futures = new ArrayList<>();
             for (RankItem item : rankItems) {
                 String vid = item.getVideoId() + "";
                 Map<String, String> rankInfo = videoBaseInfoMap.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
                 Future<Integer> future = ThreadPoolFactory.defaultPool().submit(() -> {
-                    item.norFeatureMap = getNorVideoFeature(currentMs, vid, userProfile, headInfo, rankInfo, c7Map, c8Map, userOriginInfo, historyVideoMap, videoOriginInfo);
+                    item.featureMap = getVideoFeature(currentMs, vid, userProfile, headInfo, rankInfo, c7Map, c8Map, userOriginInfo, historyVideoMap, videoOriginInfo);
+                    item.norFeatureMap = item.featureMap;
                     return 1;
                 });
                 futures.add(future);
@@ -490,11 +290,41 @@ public class RankStrategy4RegionMergeModelV564 extends RankStrategy4RegionMergeM
                     future.get(1000, TimeUnit.MILLISECONDS);
                 }
             } catch (Exception e) {
-                log.error("get nor feature error", e);
+                log.error("get feature error", e);
             }
         }
     }
 
+    private Map<String, String> getUserBaseInfo(RankParam param) {
+        Map<String, String> baseInfo = new HashMap<>();
+        String province = param.getProvince();
+        if (null != province && !province.isEmpty()) {
+            baseInfo.put("province", province.replaceAll("省$", ""));
+        }
+
+        String city = param.getCity();
+        if (null != city && !city.isEmpty()) {
+            baseInfo.put("city", city.replaceAll("市$", ""));
+        }
+
+        MachineInfo machineInfo = param.getMachineInfo();
+        if (null != machineInfo) {
+            String model = machineInfo.getModel();
+            if (null != model && !model.isEmpty()) {
+                baseInfo.put("model", model);
+            }
+            String brand = machineInfo.getBrand();
+            if (null != brand && !brand.isEmpty()) {
+                baseInfo.put("brand", brand);
+            }
+            String system = machineInfo.getSystem();
+            if (null != system && !system.isEmpty()) {
+                baseInfo.put("system", system);
+            }
+        }
+        return baseInfo;
+    }
+
     private double norPowerCalibration(double weight, double exp, double score) {
         double newScore = weight * Math.pow(score, exp);
         if (newScore > 100) {
@@ -504,4 +334,14 @@ public class RankStrategy4RegionMergeModelV564 extends RankStrategy4RegionMergeM
         }
         return newScore;
     }
+
+    private void addRecall(RankParam param, int recallNum, String recallName, Set<Long> setVideo, List<Video> rovRecallRank) {
+        if (recallNum > 0) {
+            List<Video> list = extractAndSort(param, recallName);
+            list = list.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
+            list = list.subList(0, Math.min(recallNum, list.size()));
+            rovRecallRank.addAll(list);
+            setVideo.addAll(list.stream().map(Video::getVideoId).collect(Collectors.toSet()));
+        }
+    }
 }

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV565.java

@@ -5,7 +5,6 @@ import com.tzld.piaoquan.recommend.server.common.base.RankItem;
 import com.tzld.piaoquan.recommend.server.model.Video;
 import com.tzld.piaoquan.recommend.server.service.FeatureService;
 import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
-import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
 import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
 import com.tzld.piaoquan.recommend.server.service.score.ScorerUtils;
 import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
@@ -183,13 +182,25 @@ public class RankStrategy4RegionMergeModelV565 extends RankStrategy4RegionMergeM
             Map<String, Double> featureMapDouble = item.featureMapDouble;
             item.featureMap = FeatureBucketUtils.bucketFeatureV2("20250218_bucket_322.txt", featureMapDouble);
         }
-        // 4 排序模型计算
-        double xgbRovNegRate = mergeWeight.getOrDefault("xgbRovNegRate", 0.05);
-        double calcVorMode = mergeWeight.getOrDefault("calc_vor_mode", 1d);
 
+
+        // 4.1 排序模型计算 - str
         Map<String, String> sceneFeatureMap = new HashMap<>(0);
         List<RankItem> items = ScorerUtils.getScorerPipeline("feeds_score_config_xgb_str_20250228.conf").scoring(sceneFeatureMap, userFeatureMap, rankItems);
+        // 4.2 排序模型计算 - ros
+        this.addRosScore(rankItems, userFeatureMapDouble, sceneFeatureMap);
+
         // 5 排序公式特征
+        double xgbRovNegRate = mergeWeight.getOrDefault("xgbRovNegRate", 0.05);
+
+        double calcVorMode = mergeWeight.getOrDefault("calcVorMode", 3d);
+        double calcRosMode = mergeWeight.getOrDefault("calcRosMode", 0d);
+        double calcStrMode = mergeWeight.getOrDefault("calcStrMode", 3d);
+
+
+        double rosAdd = mergeWeight.getOrDefault("ros_add", 0d);
+        double vorAdd = mergeWeight.getOrDefault("vor_add", 0d);
+
         Map<String, Map<String, String>> vid2MapFeature = this.getVideoRedisFeature(vids, "redis:vid_hasreturn_vor_4share:");
         List<Video> result = new ArrayList<>();
         for (RankItem item : items) {
@@ -197,31 +208,44 @@ public class RankStrategy4RegionMergeModelV565 extends RankStrategy4RegionMergeM
             double fmRovOrigin = item.getScoreRov();
             item.getScoresMap().put("fmRovOrigin", fmRovOrigin);
             double fmRov = restoreScore(fmRovOrigin, xgbRovNegRate);
+            fmRov = this.handleStr(fmRov, calcStrMode, item, mergeWeight);
+
             item.getScoresMap().put("fmRov", fmRov);
             item.getScoresMap().put("xgbRovNegRate", xgbRovNegRate);
-
+            item.getScoresMap().put("calcStrMode", calcStrMode);
 
             Map<String, String> vidFeatureMap = vid2MapFeature.getOrDefault(String.valueOf(item.getVideoId()), new HashMap<>());
-            double ros24h = Double.parseDouble(vidFeatureMap.getOrDefault("ros_24h", "0"));
+
+
+            double originScoreRos = item.getScoreRos();
+            double ros = this.handleRos(originScoreRos, calcRosMode, item, mergeWeight);
+
+            item.getScoresMap().put("RosXGBScore", originScoreRos);
+            item.getScoresMap().put("hasReturnRovScore", ros);
+            item.getScoresMap().put("calcRosMode", calcRosMode);
+
+
             double vor24h = Double.parseDouble(vidFeatureMap.getOrDefault("vor_24h", "0"));
-            if (calcVorMode == 1d) {
-                vor24h = ExtractorUtils.calLog(vor24h);
-            } else if (calcVorMode == 2d) {
-                double vorCoefficient = mergeWeight.getOrDefault("vor_coefficient", 1d);
-                vor24h = vorCoefficient * vor24h;
-            }
+            double vor = this.handleVor(vor24h, calcVorMode, item, mergeWeight);
 
-            item.getScoresMap().put("hasReturnRovScore", ros24h);
-            item.getScoresMap().put("vor", vor24h);
+            item.getScoresMap().put("originVor", vor24h);
+            item.getScoresMap().put("vor", vor);
             item.getScoresMap().put("calcVorMode", calcVorMode);
-            score = fmRov * (0.1 + ros24h) * (0.1 + vor24h);
 
 
+            item.getScoresMap().put("rosAdd", rosAdd);
+            item.getScoresMap().put("vorAdd", vorAdd);
+            score = fmRov * (rosAdd + ros) * (vorAdd + vor);
+
             Video video = item.getVideo();
             video.setScore(score);
             video.setSortScore(score);
             video.setScoresMap(item.getScoresMap());
-            video.setAllFeatureMap(item.getAllFeatureMap());
+
+            Map<String, String> allFeatureMap = new HashMap<>();
+            item.getFeatureMapDouble().forEach((key, value) -> allFeatureMap.put(key, String.valueOf(value)));
+            video.setAllFeatureMap(allFeatureMap);
+
             if (MapUtils.isNotEmpty(feature.getVideoFeature()) && MapUtils.isNotEmpty(feature.getVideoFeature().get(item.getVideoId() + ""))) {
                 video.getMetaFeatureMap().putAll(feature.getVideoFeature().get(item.getVideoId() + ""));
             }
@@ -234,6 +258,10 @@ public class RankStrategy4RegionMergeModelV565 extends RankStrategy4RegionMergeM
             if (MapUtils.isNotEmpty(feature.getUserFeature())) {
                 video.getMetaFeatureMap().putAll(feature.getUserFeature());
             }
+
+            // 将空的特征表过滤
+            video.getMetaFeatureMap().entrySet().removeIf(e -> MapUtils.isEmpty(e.getValue()));
+
             result.add(video);
         }
         result.sort(Comparator.comparingDouble(o -> -o.getSortScore()));
@@ -243,4 +271,34 @@ public class RankStrategy4RegionMergeModelV565 extends RankStrategy4RegionMergeM
         return result;
     }
 
+    /**
+     * ros模型打分
+     */
+    private void addRosScore(List<RankItem> rankItems, Map<String, Double> userFeatureMapDouble, Map<String, String> sceneFeatureMap) {
+        List<RankItem> rosRankItems = new ArrayList<>(rankItems.size());
+        for (RankItem rankItem : rankItems) {
+            RankItem rosRankItem = new RankItem(rankItem.getVideo());
+            // 复用了str的二分类xgboost score，所以和str保持一致
+            rosRankItem.featureMap = FeatureBucketUtils.bucketFeatureV2("20250306_ros_bucket_229.txt", rankItem.featureMapDouble);
+            rosRankItems.add(rosRankItem);
+        }
+        Map<String, String> userFeatureMap = FeatureBucketUtils.bucketFeatureV2("20250306_ros_bucket_229.txt", userFeatureMapDouble);
+        ScorerUtils.getScorerPipeline("feeds_score_config_xgb_ros_binary_20250319.conf").scoring(sceneFeatureMap, userFeatureMap, rosRankItems);
+
+        // 将ros分数补充到之前的列表中
+        Map<Long, RankItem> vidRosMap = new HashMap<>(rosRankItems.size());
+        for (RankItem rosRankItem : rosRankItems) {
+            vidRosMap.put(rosRankItem.getVideoId(), rosRankItem);
+        }
+
+        for (RankItem rankItem : rankItems) {
+            if (vidRosMap.containsKey(rankItem.getVideoId())) {
+                RankItem rosRankItem = vidRosMap.get(rankItem.getVideoId());
+
+                // 复用了rov的xgboost model类，所以取scoreRov的值
+                rankItem.setScoreRos(rosRankItem.getScoreRov());
+                rankItem.getScoresMap().put("RosXGBScore", rosRankItem.getScoreRov());
+            }
+        }
+    }
 }

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV566.java

@@ -2,14 +2,16 @@ package com.tzld.piaoquan.recommend.server.service.rank.strategy;
 
 import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
 import com.tzld.piaoquan.recommend.server.model.Video;
+import com.tzld.piaoquan.recommend.server.service.FeatureService;
 import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
-import com.tzld.piaoquan.recommend.server.util.MathUtil;
 import lombok.extern.slf4j.Slf4j;
-import org.apache.commons.math3.util.Pair;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Service;
 
-import java.util.*;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
 
 @Service
 @Slf4j
@@ -21,32 +23,26 @@ public class RankStrategy4RegionMergeModelV566 extends RankStrategy4RegionMergeM
     private RankStrategy4RegionMergeModelV563 modelV563Service;
 
     @Autowired
-    private RankStrategy4RegionMergeModelV564 modelV564Service;
+    private FeatureService featureService;
 
     @Override
     public List<Video> mergeAndRankRovRecall(RankParam param) {
         Map<String, Double> mergeWeight = this.mergeWeight != null ? this.mergeWeight : new HashMap<>(0);
 
-        List<Video> result;
-        String rosScoreKey;
-        int baseRankId = mergeWeight.getOrDefault("baseRankId", 563D).intValue();
-        if (564 == baseRankId) {
-            rosScoreKey = "NorXGBScore";
-            result = modelV564Service.mergeAndRankRovRecall(param);
-        } else {
-            rosScoreKey = "hasReturnRovScore";
-            result = modelV563Service.mergeAndRankRovRecall(param);
-        }
+        List<Video> result = modelV563Service.mergeAndRankRovRecall(param);
         if (null != result && !result.isEmpty()) {
             try {
                 Integer versionCode = param.getVersionCode();
                 int orderVersionCode = mergeWeight.getOrDefault("orderVersionCode", 1500D).intValue();
                 if (null != versionCode && versionCode == orderVersionCode) {
-                    int keepTopN = mergeWeight.getOrDefault("keepTopN", 1D).intValue();
-                    boolean useRandFlag = mergeWeight.getOrDefault("useRandFlag", 0D).intValue() > 0;
-                    boolean firstRovFlag = mergeWeight.getOrDefault("firstRovFlag", 1D).intValue() > 0;
-                    double rovRandRate = mergeWeight.getOrDefault("rovRandRate", 0.5);
-                    return resort(keepTopN, useRandFlag, firstRovFlag, rovRandRate, rosScoreKey, result);
+                    int minBid = mergeWeight.getOrDefault("minBid", 39D).intValue();
+                    int keepPageNum = mergeWeight.getOrDefault("keepPageNum", 1D).intValue();
+                    if (param.getPageNum() > keepPageNum && highlyActiveUser(param.getMid(), minBid)) {
+                        int group1Size = mergeWeight.getOrDefault("group1Size", 4D).intValue();
+                        int group2Size = mergeWeight.getOrDefault("group2Size", 8D).intValue();
+                        int group3Size = mergeWeight.getOrDefault("group3Size", 0D).intValue();
+                        return resort(group1Size, group2Size, group3Size, result);
+                    }
                 }
             } catch (Exception e) {
                 log.error("diversity resort error", e);
@@ -55,60 +51,65 @@ public class RankStrategy4RegionMergeModelV566 extends RankStrategy4RegionMergeM
         return result;
     }
 
-    private List<Video> resort(int keepTopN, boolean useRandFlag, boolean firstRovFlag, double rovRandRate, String rosScoreKey, List<Video> videos) {
-        Map<Long, Video> videoMap = new HashMap<>();
-        List<Pair<Long, Double>> rovList = new ArrayList<>();
-        List<Pair<Long, Double>> rosList = new ArrayList<>();
-        for (Video video : videos) {
-            long vid = video.getVideoId();
-            videoMap.put(vid, video);
-
-            Map<String, Double> scoreMap = video.getScoresMap();
-            rovList.add(Pair.create(vid, scoreMap.getOrDefault("fmRov", 0d)));
-            rosList.add(Pair.create(vid, scoreMap.getOrDefault(rosScoreKey, 0d)));
+    private List<Video> resort(int group1Size, int group2Size, int group3Size, List<Video> videos) {
+        // split
+        List<Video> group1 = new ArrayList<>();
+        List<Video> group2 = new ArrayList<>();
+        List<Video> group3 = new ArrayList<>();
+        List<Video> group4 = new ArrayList<>();
+        for (int i = 0; i < videos.size(); i++) {
+            if (i < group1Size) {
+                group1.add(videos.get(i));
+            } else if (i < group2Size) {
+                group2.add(videos.get(i));
+            } else if (i < group3Size) {
+                group3.add(videos.get(i));
+            } else {
+                group4.add(videos.get(i));
+            }
         }
-        rovList.sort(Comparator.comparingDouble(o -> -o.getSecond()));
-        rosList.sort(Comparator.comparingDouble(o -> -o.getSecond()));
 
-        // top
-        Set<Long> hit = new HashSet<>();
-        List<Video> result = new ArrayList<>();
-        for (int i = 0; i < keepTopN && i < videos.size(); i++) {
-            Video video = videos.get(i);
-            hit.add(video.getVideoId());
-            result.add(video);
-        }
+        // merge
+        List<List<Video>> groupList = new ArrayList<>();
+        groupList.add(group1);
+        groupList.add(group2);
+        groupList.add(group3);
+        List<Video> result = fillVideo(groupList);
+        result.addAll(group4);
+        return result;
+    }
 
-        // alternate
-        int rovIndex = 0;
-        int rosIndex = 0;
-        boolean flag = firstRovFlag;
-        for (int i = keepTopN; i < videos.size(); i++) {
-            if (useRandFlag) {
-                flag = MathUtil.nextDouble(0, 1) < rovRandRate;
-            }
-            if (flag) {
-                rovIndex = fillVideo(rovIndex, rovList, videoMap, hit, result);
-            } else {
-                rosIndex = fillVideo(rosIndex, rosList, videoMap, hit, result);
+    private List<Video> fillVideo(List<List<Video>> groupList) {
+        List<Video> result = new ArrayList<>();
+        int maxSize = getMaxSize(groupList);
+        for (int i = 0; i < maxSize; i++) {
+            for (List<Video> group : groupList) {
+                if (null != group && i < group.size()) {
+                    result.add(group.get(i));
+                }
             }
-            flag = !flag;
         }
         return result;
     }
 
-    private int fillVideo(int start, List<Pair<Long, Double>> list, Map<Long, Video> videoMap, Set<Long> hit, List<Video> result) {
-        for (int i = start; i < list.size(); i++) {
-            start++;
-            Pair<Long, Double> pair = list.get(i);
-            long vid = pair.getFirst();
-            if (!hit.contains(vid)) {
-                Video video = videoMap.get(vid);
-                hit.add(vid);
-                result.add(video);
-                break;
+    private int getMaxSize(List<List<Video>> groupList) {
+        int maxSize = 0;
+        if (null != groupList) {
+            for (List<Video> group : groupList) {
+                if (null != group) {
+                    maxSize = Math.max(maxSize, group.size());
+                }
             }
         }
-        return start;
+        return maxSize;
+    }
+
+    private boolean highlyActiveUser(String mid, int minBid) {
+        Map<String, String> userInfo = featureService.getUserInfo("alg_recsys_feature_user_active_level", mid);
+        if (null != userInfo && userInfo.containsKey("bid")) {
+            int bid = Integer.parseInt(userInfo.get("bid"));
+            return bid >= minBid;
+        }
+        return false;
     }
 }

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV567.java

@@ -1,21 +1,15 @@
 package com.tzld.piaoquan.recommend.server.service.rank.strategy;
 
-import com.alibaba.fastjson.JSON;
 import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
 import com.tzld.piaoquan.recommend.server.common.ThreadPoolFactory;
 import com.tzld.piaoquan.recommend.server.common.base.RankItem;
 import com.tzld.piaoquan.recommend.server.model.Video;
 import com.tzld.piaoquan.recommend.server.service.FeatureService;
 import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
-import com.tzld.piaoquan.recommend.server.service.rank.bo.UserSRBO;
-import com.tzld.piaoquan.recommend.server.service.rank.bo.UserShareReturnProfile;
 import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
-import com.tzld.piaoquan.recommend.server.service.rank.tansform.NORFeature;
 import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
 import com.tzld.piaoquan.recommend.server.service.score.ScorerUtils;
 import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
-import com.tzld.piaoquan.recommend.server.util.FeatureBucketUtils;
-import com.tzld.piaoquan.recommend.server.util.JSONUtils;
 import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.collections4.MapUtils;
 import org.apache.commons.math3.util.Pair;
@@ -44,7 +38,6 @@ public class RankStrategy4RegionMergeModelV567 extends RankStrategy4RegionMergeM
         //-------------------逻-------------------
         //-------------------辑-------------------
 
-        long currentMs = System.currentTimeMillis();
         List<Video> oldRovs = new ArrayList<>();
         oldRovs.addAll(extractAndSort(param, RegionHRecallStrategy.PUSH_FORM));
         oldRovs.addAll(extractAndSort(param, RegionHDupRecallStrategy.PUSH_FORM));
@@ -84,18 +77,6 @@ public class RankStrategy4RegionMergeModelV567 extends RankStrategy4RegionMergeM
         sceneCFRosn = sceneCFRosn.subList(0, Math.min(mergeWeight.getOrDefault("sceneCFRosn", 5.0).intValue(), sceneCFRosn.size()));
         rovRecallRank.addAll(sceneCFRosn);
         setVideo.addAll(sceneCFRosn.stream().map(Video::getVideoId).collect(Collectors.toSet()));
-        // -------------------cate1------------------
-        int cate1RecallN = mergeWeight.getOrDefault("cate1RecallN", 5.0).intValue();
-        addRecall(param, cate1RecallN, UserCate1RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
-        // -------------------cate2------------------
-        int cate2RecallN = mergeWeight.getOrDefault("cate2RecallN", 5.0).intValue();
-        addRecall(param, cate2RecallN, UserCate2RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
-        // -------------------head province cate1------------------
-        int headCate1RecallN = mergeWeight.getOrDefault("headCate1RecallN", 5.0).intValue();
-        addRecall(param, headCate1RecallN, HeadProvinceCate1RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
-        // -------------------head province cate2------------------
-        int headCate2RecallN = mergeWeight.getOrDefault("headCate2RecallN", 5.0).intValue();
-        addRecall(param, headCate2RecallN, HeadProvinceCate2RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
 
         //-------------------排-------------------
         //-------------------序-------------------
@@ -106,18 +87,13 @@ public class RankStrategy4RegionMergeModelV567 extends RankStrategy4RegionMergeM
         List<String> vids = CommonCollectionUtils.toListDistinct(rovRecallRank, v -> String.valueOf(v.getVideoId()));
 
         // k1:视频、k2:表、k3:特征、v:特征值
+        String provinceCn = param.getProvince().replaceAll("省$", "");
         String headVid = String.valueOf(param.getHeadVid());
-        Map<String, Map<String, Map<String, String>>> videoBaseInfoMap = featureService.getVideoBaseInfo(headVid, vids);
-        FeatureService.Feature feature = featureService.getFeatureV3(param, videoBaseInfoMap, vids);
+        FeatureService.Feature feature = featureService.getFeature(param.getMid(), vids,
+                String.valueOf(param.getAppType()), provinceCn, headVid);
         Map<String, Map<String, String>> featureOriginUser = feature.getUserFeature();
         Map<String, Map<String, Map<String, String>>> featureOriginVideo = feature.getVideoFeature();
-        Map<String, String> headVideoInfo = videoBaseInfoMap.getOrDefault(headVid, new HashMap<>()).getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
 
-        // 用户信息预处理
-        Map<String, Map<String, String[]>> newC7Map = NORFeature.parseUCFScore(featureOriginUser.getOrDefault("alg_mid_feature_sharecf", new HashMap<>()));
-        Map<String, Map<String, String[]>> newC8Map = NORFeature.parseUCFScore(featureOriginUser.getOrDefault("alg_mid_feature_returncf", new HashMap<>()));
-        UserShareReturnProfile userProfile = parseUserProfile(featureOriginUser);
-        Map<String, Map<String, String>> userBehaviorVideoMap = getUserBehaviorVideoMap(userProfile);
 
         // 2 特征处理
         Map<String, Double> userFeatureMapDouble = new HashMap<>();
@@ -248,7 +224,7 @@ public class RankStrategy4RegionMergeModelV567 extends RankStrategy4RegionMergeM
                 }
             }
 
-            Map<String, String> videoInfo = videoBaseInfoMap.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
+            Map<String, String> videoInfo = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
             featureMap.put("total_time", Double.parseDouble(videoInfo.getOrDefault("total_time", "0")));
             featureMap.put("bit_rate", Double.parseDouble(videoInfo.getOrDefault("bit_rate", "0")));
 
@@ -305,11 +281,6 @@ public class RankStrategy4RegionMergeModelV567 extends RankStrategy4RegionMergeM
             item.featureMapDouble = featureMap;
         }
 
-        // get nor feature
-        Map<String, String> norUserFeatureMap = getNorUserFeature(currentMs, headVideoInfo, userProfile, featureOriginUser);
-        batchGetNorVideoFeature(currentMs, userProfile, headVideoInfo, videoBaseInfoMap,
-                newC7Map, newC8Map, featureOriginUser, userBehaviorVideoMap, featureOriginVideo, rankItems);
-
         // 3 连续值特征分桶
         readBucketFile();
         Map<String, String> userFeatureMap = new HashMap<>(userFeatureMapDouble.size());
@@ -342,27 +313,67 @@ public class RankStrategy4RegionMergeModelV567 extends RankStrategy4RegionMergeM
             item.featureMap = featureMap;
         }
         // 4 排序模型计算
-        double xgbNorPowerWeight = mergeWeight.getOrDefault("xgbNorPowerWeight", 1.22);
-        double xgbNorPowerExp = mergeWeight.getOrDefault("xgbNorPowerExp", 1.24);
         Map<String, String> sceneFeatureMap = new HashMap<>(0);
-        List<RankItem> items = ScorerUtils.getScorerPipeline("feeds_score_config_fm_xgb_20250303.conf").scoring(sceneFeatureMap, userFeatureMap, norUserFeatureMap, rankItems);
+        List<RankItem> items = ScorerUtils.getScorerPipeline("feeds_score_config_20240807.conf").scoring(sceneFeatureMap, userFeatureMap, rankItems);
         // 5 排序公式特征
         Map<String, Map<String, String>> vid2MapFeature = this.getVideoRedisFeature(vids, "redis:vid_hasreturn_vor:");
+
+        // Ros增强传播因子
+        Map<String, Map<String, String>> rosSpreadDivMap = this.getVideoRedisFeature(vids, "vid_for_spread:");
+
         List<Video> result = new ArrayList<>();
+
+        double calcVorMode = mergeWeight.getOrDefault("calcVorMode", 3d);
+        double calcRosMode = mergeWeight.getOrDefault("calcRosMode", 0d);
+        double calcStrMode = mergeWeight.getOrDefault("calcStrMode", 3d);
+
+        double rosAdd = mergeWeight.getOrDefault("ros_add", 0.1d);
+        double ros2Multi = mergeWeight.getOrDefault("ros2_multi", 1d);
+        double vorAdd = mergeWeight.getOrDefault("vor_add", 0d);
+
+        double rosSpreadDivisorIndex = mergeWeight.getOrDefault("rosSpreadDivisorIndex", 2d);
+        String spreadDivisorKey = this.indexCoverKey(rosSpreadDivisorIndex);
+        log.info("567 spreadDivisorKey is: {}", spreadDivisorKey);
+
         for (RankItem item : items) {
             double score;
             double fmRovOrigin = item.getScoreRov();
             item.getScoresMap().put("fmRovOrigin", fmRovOrigin);
-            double fmRov = restoreScore(fmRovOrigin);
-            item.getScoresMap().put("fmRov", fmRov);
-            double hasReturnRovScore = Double.parseDouble(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()).getOrDefault("rov", "0"));
-            item.getScoresMap().put("hasReturnRovScore", hasReturnRovScore);
-            double norXGBScore = item.getScoresMap().getOrDefault("NorXGBScore", 0d);
-            double newNorXGBScore = norPowerCalibration(xgbNorPowerWeight, xgbNorPowerExp, norXGBScore);
-            double vor = Double.parseDouble(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()).getOrDefault("vor", "0"));
+            double str = restoreScore(fmRovOrigin);
+            item.getScoresMap().put("originStr", str);
+            str = this.handleStr(str, calcStrMode, item, mergeWeight);
+            item.getScoresMap().put("xgbRovNegRate", 0.9d);
+            item.getScoresMap().put("fmRov", str);
+            item.getScoresMap().put("str", str);
+            item.getScoresMap().put("calcStrMode", calcStrMode);
+
+            double originRos = Double.parseDouble(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()).getOrDefault("rov", "0"));
+            double ros = this.handleRos(originRos, calcRosMode, item, mergeWeight);
+            item.getScoresMap().put("hasReturnRovScore", ros);
+            item.getScoresMap().put("ros", ros);
+            item.getScoresMap().put("originRos", originRos);
+            item.getScoresMap().put("calcRosMode", calcRosMode);
+
+            String spreadDivStr = rosSpreadDivMap.getOrDefault(String.valueOf(item.getVideoId()), new HashMap<>()).getOrDefault(spreadDivisorKey, "0");
+            double rosSpreadDiv = Double.parseDouble(spreadDivStr);
+            item.getScoresMap().put("rosSpreadDiv", rosSpreadDiv);
+
+            double originVor = Double.parseDouble(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()).getOrDefault("vor", "0"));
+            double vor = this.handleVor(originVor, calcVorMode, item, mergeWeight);
+            item.getScoresMap().put("originVor", originVor);
             item.getScoresMap().put("vor", vor);
-            score = fmRov * (0.1 + newNorXGBScore) * (0.1 + vor);
+            item.getScoresMap().put("calcVorMode", calcVorMode);
+
+
+            item.getScoresMap().put("rosAdd", rosAdd);
+            item.getScoresMap().put("vorAdd", vorAdd);
+            item.getScoresMap().put("ros2Multi", ros2Multi);
+            item.getScoresMap().put("rosSpreadDivisorIndex", rosSpreadDivisorIndex);
+            score = str * (rosAdd + ros + ros2Multi * rosSpreadDiv) * (vorAdd + vor);
+
             Video video = item.getVideo();
+            video.setScoreStr(str);
+            video.setScoreRos(rosAdd + ros + ros2Multi * rosSpreadDiv);
             video.setScore(score);
             video.setSortScore(score);
             video.setScoresMap(item.getScoresMap());
@@ -370,12 +381,6 @@ public class RankStrategy4RegionMergeModelV567 extends RankStrategy4RegionMergeM
             if (MapUtils.isNotEmpty(feature.getVideoFeature()) && MapUtils.isNotEmpty(feature.getVideoFeature().get(item.getVideoId() + ""))) {
                 video.getMetaFeatureMap().putAll(feature.getVideoFeature().get(item.getVideoId() + ""));
             }
-            if (MapUtils.isNotEmpty(videoBaseInfoMap) && MapUtils.isNotEmpty(videoBaseInfoMap.get(item.getVideoId() + ""))) {
-                video.getMetaFeatureMap().putAll(videoBaseInfoMap.get(item.getVideoId() + ""));
-            }
-            if (MapUtils.isNotEmpty(headVideoInfo)) {
-                video.getMetaFeatureMap().put("head_video", headVideoInfo);
-            }
             if (MapUtils.isNotEmpty(feature.getUserFeature())) {
                 video.getMetaFeatureMap().putAll(feature.getUserFeature());
             }
@@ -385,145 +390,17 @@ public class RankStrategy4RegionMergeModelV567 extends RankStrategy4RegionMergeM
         return result;
     }
 
-    private UserShareReturnProfile parseUserProfile(Map<String, Map<String, String>> userOriginInfo) {
-        if (null != userOriginInfo) {
-            Map<String, String> c9 = userOriginInfo.get("alg_recsys_feature_user_share_return_stat");
-            if (null != c9 && !c9.isEmpty()) {
-                String c9Str = JSONUtils.toJson(c9);
-                if (!c9Str.isEmpty()) {
-                    try {
-                        return JSON.parseObject(c9Str, UserShareReturnProfile.class);
-                    } catch (Exception e) {
-                        log.error("parseObject user profile error! value=[{}]", c9Str, e);
-                    }
-                }
-            }
-        }
-        return null;
-    }
-
-    private Map<String, Map<String, String>> getUserBehaviorVideoMap(UserShareReturnProfile userProfile) {
-        Set<String> vidSet = new HashSet<>();
-        if (null != userProfile) {
-            for (List<UserSRBO> list : Arrays.asList(userProfile.getM_s_s(), userProfile.getM_r_s(), userProfile.getL_s_s(), userProfile.getL_r_s())) {
-                if (null != list) {
-                    for (UserSRBO u : list) {
-                        if (null != u) {
-                            vidSet.add(u.getId() + "");
-                        }
-                    }
-                }
-            }
-        }
-
-        Map<String, Map<String, String>> historyVideoMap = new HashMap<>();
-        if (!vidSet.isEmpty()) {
-            Map<String, Map<String, Map<String, String>>> videoMap = featureService.getVideoBaseInfo("", new ArrayList<>(vidSet));
-            if (null != videoMap && !videoMap.isEmpty()) {
-                for (Map.Entry<String, Map<String, Map<String, String>>> entry : videoMap.entrySet()) {
-                    String vid = entry.getKey();
-                    Map<String, Map<String, String>> map = entry.getValue();
-                    if (null != map && map.containsKey("alg_vid_feature_basic_info")) {
-                        historyVideoMap.put(vid, map.get("alg_vid_feature_basic_info"));
-                    }
-                }
-            }
-        }
-        return historyVideoMap;
-    }
-
-    private Map<String, String> getNorUserFeature(long currentMs, Map<String, String> headInfo, UserShareReturnProfile userProfile, Map<String, Map<String, String>> userOriginInfo) {
-        Map<String, Double> featMap = new HashMap<>();
-        // context feature
-        NORFeature.getContextFeature(currentMs, featMap);
-
-        // head video feature
-        NORFeature.getVideoBaseFeature("h", currentMs, headInfo, featMap);
-
-        // user feature
-        NORFeature.getUserFeature(userOriginInfo, featMap);
-        NORFeature.getUserProfileFeature(userProfile, featMap);
-
-        return FeatureBucketUtils.noBucketFeature(featMap);
-    }
-
-    private Map<String, String> getNorVideoFeature(long currentMs, String vid,
-                                                   UserShareReturnProfile userProfile,
-                                                   Map<String, String> headInfo, Map<String, String> rankInfo,
-                                                   Map<String, Map<String, String[]>> c7Map,
-                                                   Map<String, Map<String, String[]>> c8Map,
-                                                   Map<String, Map<String, String>> userOriginInfo,
-                                                   Map<String, Map<String, String>> historyVideoMap,
-                                                   Map<String, Map<String, Map<String, String>>> videoOriginInfo) {
-        Map<String, Double> featMap = new HashMap<>();
-        // user & video feature
-        NORFeature.getUserTagsCrossVideoFeature("c5", rankInfo, userOriginInfo.get("alg_mid_feature_return_tags"), featMap);
-        NORFeature.getUserTagsCrossVideoFeature("c6", rankInfo, userOriginInfo.get("alg_mid_feature_share_tags"), featMap);
-        NORFeature.getUserCFFeature("c7", vid, c7Map, featMap);
-        NORFeature.getUserCFFeature("c8", vid, c8Map, featMap);
-
-        // rank video feature
-        NORFeature.getVideoBaseFeature("r", currentMs, rankInfo, featMap);
-        NORFeature.getVideoFeature(vid, videoOriginInfo, featMap);
-
-        // head&rank cross feature
-        NORFeature.getHeadRankVideoCrossFeature(headInfo, rankInfo, featMap);
-
-        // user profile & rank cross
-        NORFeature.getProfileVideoCrossFeature(currentMs, userProfile, rankInfo, historyVideoMap, featMap);
-
-        return FeatureBucketUtils.noBucketFeature(featMap);
-    }
-
-    private void batchGetNorVideoFeature(long currentMs,
-                                         UserShareReturnProfile userProfile,
-                                         Map<String, String> headInfo,
-                                         Map<String, Map<String, Map<String, String>>> videoBaseInfoMap,
-                                         Map<String, Map<String, String[]>> c7Map,
-                                         Map<String, Map<String, String[]>> c8Map,
-                                         Map<String, Map<String, String>> userOriginInfo,
-                                         Map<String, Map<String, String>> historyVideoMap,
-                                         Map<String, Map<String, Map<String, String>>> videoOriginInfo,
-                                         List<RankItem> rankItems) {
-        if (null != rankItems && !rankItems.isEmpty()) {
-            List<Future<Integer>> futures = new ArrayList<>();
-            for (RankItem item : rankItems) {
-                String vid = item.getVideoId() + "";
-                Map<String, String> rankInfo = videoBaseInfoMap.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
-                Future<Integer> future = ThreadPoolFactory.defaultPool().submit(() -> {
-                    item.norFeatureMap = getNorVideoFeature(currentMs, vid, userProfile, headInfo, rankInfo, c7Map, c8Map, userOriginInfo, historyVideoMap, videoOriginInfo);
-                    return 1;
-                });
-                futures.add(future);
-            }
-
-            try {
-                for (Future<Integer> future : futures) {
-                    future.get(1000, TimeUnit.MILLISECONDS);
-                }
-            } catch (Exception e) {
-                log.error("get nor feature error", e);
-            }
+    private String indexCoverKey(double index) {
+        switch (String.valueOf(index)) {
+            case "1":
+                return "head_video_rov1";
+            case "3":
+                return "head_video_recommend_rovn";
+            case "4":
+                return "head_video_recommend_fission_rate";
+            default:
+                return "recommend_123_depth_fission_rate";
         }
     }
 
-    private double norPowerCalibration(double weight, double exp, double score) {
-        double newScore = weight * Math.pow(score, exp);
-        if (newScore > 100) {
-            newScore = 100;
-        } else if (newScore < score) {
-            newScore = score;
-        }
-        return newScore;
-    }
-
-    private void addRecall(RankParam param, int recallNum, String recallName, Set<Long> setVideo, List<Video> rovRecallRank) {
-        if (recallNum > 0) {
-            List<Video> list = extractAndSort(param, recallName);
-            list = list.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
-            list = list.subList(0, Math.min(recallNum, list.size()));
-            rovRecallRank.addAll(list);
-            setVideo.addAll(list.stream().map(Video::getVideoId).collect(Collectors.toSet()));
-        }
-    }
 }

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV568.java

@@ -20,6 +20,7 @@ import org.springframework.stereotype.Service;
 import java.util.*;
 import java.util.concurrent.Future;
 import java.util.concurrent.TimeUnit;
+import java.util.regex.Matcher;
 import java.util.stream.Collectors;
 
 @Service
@@ -38,6 +39,8 @@ public class RankStrategy4RegionMergeModelV568 extends RankStrategy4RegionMergeM
         //-------------------合-------------------
         //-------------------逻-------------------
         //-------------------辑-------------------
+        Set<Long> setVideo = new HashSet<>();
+        List<Video> rovRecallRank = new ArrayList<>();
 
         List<Video> oldRovs = new ArrayList<>();
         oldRovs.addAll(extractAndSort(param, RegionHRecallStrategy.PUSH_FORM));
@@ -50,44 +53,58 @@ public class RankStrategy4RegionMergeModelV568 extends RankStrategy4RegionMergeM
         List<Video> v0 = oldRovs.size() <= sizeReturn
                 ? oldRovs
                 : oldRovs.subList(0, sizeReturn);
-        Set<Long> setVideo = new HashSet<>();
-        this.duplicate(setVideo, v0);
-        setVideo.addAll(v0.stream().map(Video::getVideoId).collect(Collectors.toSet()));
-        List<Video> rovRecallRank = new ArrayList<>(v0);
-        //-------------------return相似召回------------------
-        List<Video> v6 = extractAndSort(param, ReturnVideoRecallStrategy.PUSH_FORM);
-        v6 = v6.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
-        v6 = v6.subList(0, Math.min(mergeWeight.getOrDefault("v6", 5.0).intValue(), v6.size()));
-        rovRecallRank.addAll(v6);
-        setVideo.addAll(v6.stream().map(Video::getVideoId).collect(Collectors.toSet()));
-        //-------------------新地域召回------------------
-        List<Video> v1 = extractAndSort(param, RegionRealtimeRecallStrategyV1.PUSH_FORM);
-        v1 = v1.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
-        v1 = v1.subList(0, Math.min(mergeWeight.getOrDefault("v1", 5.0).intValue(), v1.size()));
-        rovRecallRank.addAll(v1);
-        setVideo.addAll(v1.stream().map(Video::getVideoId).collect(Collectors.toSet()));
-        //-------------------scene cf rovn------------------
-        List<Video> sceneCFRovn = extractAndSort(param, SceneCFRovnRecallStrategy.PUSH_FORM);
-        sceneCFRovn = sceneCFRovn.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
-        sceneCFRovn = sceneCFRovn.subList(0, Math.min(mergeWeight.getOrDefault("sceneCFRovn", 5.0).intValue(), sceneCFRovn.size()));
-        rovRecallRank.addAll(sceneCFRovn);
-        setVideo.addAll(sceneCFRovn.stream().map(Video::getVideoId).collect(Collectors.toSet()));
-        //-------------------scene cf rosn------------------
-        List<Video> sceneCFRosn = extractAndSort(param, SceneCFRosnRecallStrategy.PUSH_FORM);
-        sceneCFRosn = sceneCFRosn.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
-        sceneCFRosn = sceneCFRosn.subList(0, Math.min(mergeWeight.getOrDefault("sceneCFRosn", 5.0).intValue(), sceneCFRosn.size()));
-        rovRecallRank.addAll(sceneCFRosn);
-        setVideo.addAll(sceneCFRosn.stream().map(Video::getVideoId).collect(Collectors.toSet()));
-        if (FeatureUtils.lowFissionChannel(param.getRootSourceId())) {
-            // head cate1 str
-            int headCate1StrN = mergeWeight.getOrDefault("headCate1StrN", 5.0).intValue();
-            addRecall(param, headCate1StrN, HeadCate1STRRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
-            // head cate2 str
-            int headCate2StrN = mergeWeight.getOrDefault("headCate2StrN", 5.0).intValue();
-            addRecall(param, headCate2StrN, HeadCate2STRRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
-            // province str
-            int provinceStrN = mergeWeight.getOrDefault("provinceStrN", 5.0).intValue();
-            addRecall(param, provinceStrN, ProvinceSTRRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        //this.duplicate(setVideo, v0);
+
+        Matcher matcher = FeatureUtils.getChannelMatcher(param.getRootSourceId());
+        if (null != matcher && matcher.find() && FeatureUtils.firstLevel(param.getUserShareDepth())) {
+            //-------------------return相似召回------------------
+            List<Video> v6 = extractAndSort(param, ReturnVideoRecallStrategy.PUSH_FORM);
+            v6 = v6.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
+            v6 = v6.subList(0, Math.min(mergeWeight.getOrDefault("v6", 4.0).intValue(), v6.size()));
+            rovRecallRank.addAll(v6);
+            setVideo.addAll(v6.stream().map(Video::getVideoId).collect(Collectors.toSet()));
+            // channel rovn
+            int channelROVN = mergeWeight.getOrDefault("channelROVN", 4.0).intValue();
+            addRecall(param, channelROVN, ChannelROVRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+            // 老地域
+            v0 = v0.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
+            rovRecallRank.addAll(v0);
+            setVideo.addAll(v0.stream().map(Video::getVideoId).collect(Collectors.toSet()));
+
+            // 是否排序
+            boolean firstLevelRank = mergeWeight.getOrDefault("firstLevelRank", 0D).intValue() > 0;
+            if (!firstLevelRank) {
+                return rovRecallRank;
+            }
+        } else {
+            // 老地域
+            v0 = v0.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
+            rovRecallRank.addAll(v0);
+            setVideo.addAll(v0.stream().map(Video::getVideoId).collect(Collectors.toSet()));
+            //-------------------return相似召回------------------
+            List<Video> v6 = extractAndSort(param, ReturnVideoRecallStrategy.PUSH_FORM);
+            v6 = v6.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
+            v6 = v6.subList(0, Math.min(mergeWeight.getOrDefault("v6", 5.0).intValue(), v6.size()));
+            rovRecallRank.addAll(v6);
+            setVideo.addAll(v6.stream().map(Video::getVideoId).collect(Collectors.toSet()));
+            //-------------------新地域召回------------------
+            List<Video> v1 = extractAndSort(param, RegionRealtimeRecallStrategyV1.PUSH_FORM);
+            v1 = v1.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
+            v1 = v1.subList(0, Math.min(mergeWeight.getOrDefault("v1", 5.0).intValue(), v1.size()));
+            rovRecallRank.addAll(v1);
+            setVideo.addAll(v1.stream().map(Video::getVideoId).collect(Collectors.toSet()));
+            //-------------------scene cf rovn------------------
+            List<Video> sceneCFRovn = extractAndSort(param, SceneCFRovnRecallStrategy.PUSH_FORM);
+            sceneCFRovn = sceneCFRovn.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
+            sceneCFRovn = sceneCFRovn.subList(0, Math.min(mergeWeight.getOrDefault("sceneCFRovn", 5.0).intValue(), sceneCFRovn.size()));
+            rovRecallRank.addAll(sceneCFRovn);
+            setVideo.addAll(sceneCFRovn.stream().map(Video::getVideoId).collect(Collectors.toSet()));
+            //-------------------scene cf rosn------------------
+            List<Video> sceneCFRosn = extractAndSort(param, SceneCFRosnRecallStrategy.PUSH_FORM);
+            sceneCFRosn = sceneCFRosn.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
+            sceneCFRosn = sceneCFRosn.subList(0, Math.min(mergeWeight.getOrDefault("sceneCFRosn", 5.0).intValue(), sceneCFRosn.size()));
+            rovRecallRank.addAll(sceneCFRosn);
+            setVideo.addAll(sceneCFRosn.stream().map(Video::getVideoId).collect(Collectors.toSet()));
         }
 
         //-------------------排-------------------

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV569.java

@@ -196,6 +196,7 @@ public class RankStrategy4RegionMergeModelV569 extends RankStrategy4RegionMergeM
         double xgbRovNegRate = mergeWeight.getOrDefault("xgbRovNegRate", 0.05);
         double calcVorMode = mergeWeight.getOrDefault("calcVorMode", 1d);
         double calcRosMode = mergeWeight.getOrDefault("calcRosMode", 1d);
+        double calcStrMode = mergeWeight.getOrDefault("calcStrMode", 0d);
 
 
         Map<String, Map<String, String>> vid2MapFeature = this.getVideoRedisFeature(vids, "redis:vid_hasreturn_vor_4share:");
@@ -205,39 +206,35 @@ public class RankStrategy4RegionMergeModelV569 extends RankStrategy4RegionMergeM
             double fmRovOrigin = item.getScoreRov();
             item.getScoresMap().put("fmRovOrigin", fmRovOrigin);
             double fmRov = restoreScore(fmRovOrigin, xgbRovNegRate);
+            fmRov = this.handleStr(fmRov, calcStrMode, item, mergeWeight);
+
+
             item.getScoresMap().put("fmRov", fmRov);
             item.getScoresMap().put("xgbRovNegRate", xgbRovNegRate);
+            item.getScoresMap().put("calcStrMode", calcStrMode);
 
 
             Map<String, String> vidFeatureMap = vid2MapFeature.getOrDefault(String.valueOf(item.getVideoId()), new HashMap<>());
 
             double vor24h = Double.parseDouble(vidFeatureMap.getOrDefault("vor_24h", "0"));
-            if (calcVorMode == 1d) {
-                vor24h = ExtractorUtils.calLog(vor24h);
-            } else if (calcVorMode == 2d) {
-                double vorCoefficient = mergeWeight.getOrDefault("vor_coefficient", 1d);
-                item.getScoresMap().put("vorCoefficient", vorCoefficient);
-                vor24h = vorCoefficient * vor24h;
-            } else if (calcVorMode == 3d) {
-                double vorPower = mergeWeight.getOrDefault("vor_power", 1d);
-                item.getScoresMap().put("vorPower", vorPower);
-                vor24h = Math.pow(vor24h, vorPower);
-            }
+            double vor = this.handleVor(vor24h, calcVorMode, item, mergeWeight);
 
-            double originScoreRos = item.getScoreRos();
+            // double originScoreRos = item.getScoreRos();
+            double originScoreRos = Double.parseDouble(vidFeatureMap.getOrDefault("ros_24h", "0d"));
             double scoreRos = this.handleRos(originScoreRos, calcRosMode, item, mergeWeight);
 
-            double rosAdd = mergeWeight.getOrDefault("ros_add", 0.00001);
+            double rosAdd = mergeWeight.getOrDefault("ros_add", 0.1);
             double vorAdd = mergeWeight.getOrDefault("vor_add", 0.1);
 
             item.getScoresMap().put("hasReturnRovScore", scoreRos);
-            item.getScoresMap().put("vor", vor24h);
+            item.getScoresMap().put("originVor", vor24h);
+            item.getScoresMap().put("vor", vor);
             item.getScoresMap().put("calcVorMode", calcVorMode);
             item.getScoresMap().put("calcRosMode", calcRosMode);
-            item.getScoresMap().put("RosXGBScore", originScoreRos);
+            item.getScoresMap().put("originRos", originScoreRos);
             item.getScoresMap().put("rosAdd", rosAdd);
             item.getScoresMap().put("vorAdd", vorAdd);
-            score = fmRov * (rosAdd + scoreRos) * (vorAdd + vor24h);
+            score = fmRov * (rosAdd + scoreRos) * (vorAdd + vor);
 
 
             Video video = item.getVideo();
@@ -274,32 +271,6 @@ public class RankStrategy4RegionMergeModelV569 extends RankStrategy4RegionMergeM
         return result;
     }
 
-    private double handleRos(double originScoreRos, double calcRosMode, RankItem item, Map<String, Double> mergeWeight) {
-        if (originScoreRos == 0) {
-            return 0;
-        }
-
-        double scoreRos = ExtractorUtils.inverseLog(originScoreRos);
-        if (calcRosMode == 1d) {
-            double rosPower = mergeWeight.getOrDefault("le_ros_power", 5d);
-            if (scoreRos > 1) {
-                rosPower = mergeWeight.getOrDefault("gt_1_ros_poewr", 1.5d);
-            }
-            item.getScoresMap().put("rosPower", rosPower);
-            scoreRos = Math.pow(scoreRos, rosPower);
-        } else if (calcRosMode == 2d) {
-            double modelRosCoefficient = mergeWeight.getOrDefault("model_ros_coefficient", 8d);
-            item.getScoresMap().put("modelRosCoefficient", modelRosCoefficient);
-            scoreRos = ExtractorUtils.inverseLog(originScoreRos * modelRosCoefficient);
-        } else if (calcRosMode == 3d) {
-            double rosPower = mergeWeight.getOrDefault("ros_power", 5d);
-            item.getScoresMap().put("rosPower", rosPower);
-            scoreRos = Math.pow(scoreRos, rosPower);
-        }
-
-        return scoreRos;
-    }
-
     /**
      * ros模型打分
      */

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/tansform/FeatureV6.java

@@ -0,0 +1,515 @@
+package com.tzld.piaoquan.recommend.server.service.rank.tansform;
+
+import com.tzld.piaoquan.recommend.server.service.rank.bo.UserSRBO;
+import com.tzld.piaoquan.recommend.server.service.rank.bo.UserShareReturnProfile;
+import com.tzld.piaoquan.recommend.server.service.rank.bo.VideoAttrSRBO;
+import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
+import com.tzld.piaoquan.recommend.server.util.FeatureUtils;
+import com.tzld.piaoquan.recommend.server.util.SimilarityUtils;
+
+import java.util.*;
+
+public class FeatureV6 {
+    private static final int seqMaxN = 2;
+    private static final int seqLastN = 2;
+    private static final double smoothPlus = 5.0;
+    private static final double log1Scale = 10.0;
+    private static final List<String> c1Periods = Arrays.asList("72h", "168h");
+    private static final List<String> c4Periods = Arrays.asList("72h", "168h");
+    private static final List<String> b0Periods = Arrays.asList("1h", "3h", "6h", "12h");
+    private static final List<String> b1Periods = Arrays.asList("1h", "3h", "24h", "72h", "168h");
+    private static final List<String> b2Periods = Arrays.asList("1h", "3h", "24h");
+    private static final List<String> b3Periods = Arrays.asList("24h", "168h");
+    private static final List<String> b4Periods = Arrays.asList("1h", "12h");
+    private static final List<String> b5Periods = Arrays.asList("72h", "168h");
+    private static final List<String> b6Periods = Arrays.asList("1h", "24h");
+    private static final List<String> b7Periods = Arrays.asList("24h", "168h");
+    private static final List<String> b8Periods = Arrays.asList("24h");
+    private static final List<String> b9Periods = Arrays.asList("24h");
+    private static final List<String> b10Periods = Arrays.asList("1h", "12h");
+    private static final List<String> b11Periods = Arrays.asList("12h", "168h");
+    private static final List<String> b13Periods = Arrays.asList("24h", "168h");
+    private static final List<String> dayPeriods = Arrays.asList("7d", "14d", "30d", "60d");
+    private static final List<String> videoCateAttrs = Arrays.asList(FeatureUtils.cate1Attr, FeatureUtils.cate2Attr, FeatureUtils.festive1Attr, FeatureUtils.channelAttr);
+    private static final List<String> videoSimAttrs = Arrays.asList("title", "cate2", "cate2_list", "keywords");
+    private static final List<String> hVideoSimAttrs = Arrays.asList("title");
+    private static final List<String> cfList = Arrays.asList("share", "return");
+    private static final List<String> userAttrList = Arrays.asList("province", "city", "model", "brand", "system");
+    private static final Set<String> hotSceneSet = new HashSet<>(Arrays.asList("1008", "1007", "1058", "1074", "1010"));
+
+    public static void getContextFeature(long currentMs, String appType, String hotSceneType, Map<String, Double> featureMap) {
+        Calendar calendar = Calendar.getInstance();
+        calendar.setTimeInMillis(currentMs);
+
+        int week = calendar.get(Calendar.DAY_OF_WEEK);
+        int hour = calendar.get(Calendar.HOUR_OF_DAY) + 1;
+        featureMap.put(String.format("%s@%d", "week", week), 1.0);
+        featureMap.put(String.format("%s@%d", "hour", hour), 1.0);
+        featureMap.put("hour", hour * 1.0);
+        featureMap.put(String.format("%s@%s", "app", appType), 1.0);
+        String hot;
+        if (hotSceneSet.contains(hotSceneType)) {
+            hot = hotSceneType;
+        } else {
+            hot = "other";
+        }
+        featureMap.put(String.format("%s@%s", "hot", hot), 1.0);
+    }
+
+    public static void getUserFeature(Map<String, Map<String, String>> userOriginInfo, Map<String, Double> featMap) {
+        oneTypeStatFeature("c1", "return_1_uv", c1Periods, userOriginInfo.get("mid_global_feature_20250212"), featMap);
+    }
+
+    public static void getUserProfileFeature(UserShareReturnProfile profile, Map<String, String> userInfo, Map<String, Double> featMap) {
+        if (null != profile) {
+            long s_pv = profile.getS_pv();              // share_pv(分享pv)
+            long s_cnt = profile.getS_cnt();            // share_cnt(分享次数)
+            long r_pv = profile.getR_pv();              // return_pv(回流pv)
+            long r_uv = profile.getR_uv();              // return_uv(回流uv)
+            long m_s_cnt = profile.getM_s_cnt();        // max_share_cnt(最大分享次数)
+            long m_r_uv = profile.getM_r_uv();          // max_return_uv(最大回流uv)
+            if (s_pv > 0) {
+                double s_pv_s = FeatureUtils.log1(s_pv, log1Scale);
+                double s_cnt_s = FeatureUtils.log1(s_cnt, log1Scale);
+                double r_pv_s = FeatureUtils.log1(r_pv, log1Scale);
+                double r_uv_s = FeatureUtils.log1(r_uv, log1Scale);
+                double m_s_cnt_s = FeatureUtils.log1(m_s_cnt, log1Scale);
+                double m_r_uv_s = FeatureUtils.log1(m_r_uv, log1Scale);
+                double ros_one = FeatureUtils.wilsonScore(r_pv, s_pv);
+                double ros = FeatureUtils.plusSmooth(r_uv, s_pv, smoothPlus);
+                double ros_minus = FeatureUtils.plusSmooth(r_uv, r_pv, smoothPlus);
+                featMap.put("c9@s_pv", s_pv_s);
+                featMap.put("c9@s_cnt", s_cnt_s);
+                featMap.put("c9@r_pv", r_pv_s);
+                featMap.put("c9@r_uv", r_uv_s);
+                featMap.put("c9@m_s_cnt", m_s_cnt_s);
+                featMap.put("c9@m_r_uv", m_r_uv_s);
+                featMap.put("c9@ros_one", ros_one);
+                featMap.put("c9@ros", ros);
+                featMap.put("c9@ros_minus", ros_minus);
+            }
+        }
+        if (null != userInfo && !userInfo.isEmpty()) {
+            for (String attr : userAttrList) {
+                if (userInfo.containsKey(attr)) {
+                    String value = userInfo.get(attr).trim().replaceAll("(\\s+|\\t|:)", "_");
+                    if (!value.isEmpty()) {
+                        String key = String.format("%s@%s", attr, value.toLowerCase());
+                        featMap.put(key, 1.0);
+                    }
+                }
+            }
+        }
+    }
+
+    public static void getUserTagsCrossVideoFeature(String prefix, Map<String, String> videoInfo, Map<String, String> infoMap, Map<String, Double> featMap) {
+        if (null == videoInfo || videoInfo.isEmpty() || null == infoMap || infoMap.isEmpty()) {
+            return;
+        }
+        String title = videoInfo.getOrDefault("title", "");
+        if (title.isEmpty()) {
+            return;
+        }
+        for (String period : Arrays.asList("tags_1d", "tags_3d", "tags_7d")) {
+            String tags = infoMap.getOrDefault(period, "");
+            if (!tags.isEmpty()) {
+                Double[] doubles = ExtractorUtils.funcC34567ForTagsNew(tags, title);
+                featMap.put(prefix + "_" + period + "@matchnum", doubles[0]);
+                featMap.put(prefix + "_" + period + "@maxscore", doubles[1]);
+                featMap.put(prefix + "_" + period + "@avgscore", doubles[2]);
+            }
+        }
+    }
+
+    public static void getUserCFFeature(String prefix, String vid, Map<String, Map<String, String[]>> infoMap, Map<String, Double> featMap) {
+        if (vid.isEmpty() || null == infoMap || infoMap.isEmpty()) {
+            return;
+        }
+        for (String cfType : cfList) {
+            if (infoMap.containsKey(cfType)) {
+                Map<String, String[]> cfScoresMap = infoMap.get(cfType);
+                if (null != cfScoresMap && cfScoresMap.containsKey(vid)) {
+                    String[] scores = cfScoresMap.get(vid);
+                    Double score1 = Double.parseDouble(scores[0]);
+                    Double score2 = Double.parseDouble(scores[1]);
+                    Double score3 = Double.parseDouble(scores[2]) <= 0 ? 0D : 1.0 / Double.parseDouble(scores[2]);
+                    featMap.put(prefix + "_" + cfType + "@score", score1);
+                    featMap.put(prefix + "_" + cfType + "@num", score2);
+                    featMap.put(prefix + "_" + cfType + "@rank", score3);
+                }
+            }
+        }
+    }
+
+    public static void getVideoFeature(String vid, Map<String, Map<String, Map<String, String>>> videoOriginInfo, Map<String, Double> featMap) {
+        oneTypeStatFeature("b0", b0Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_recsys_feature_video_clean_stat"), featMap);
+        oneTypeStatFeature("b1", "return_1_uv", b1Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_vid_global_feature_20250212"), featMap);
+        oneTypeStatFeature("b2", "return_n_uv", b2Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_vid_recommend_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b3", "return_n_uv", b3Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_vid_recommend_flowpool_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b4", "return_n_uv", b4Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_vid_apptype_recommend_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b5", "return_n_uv", b5Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_vid_province_recommend_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b6", "return_n_uv", b6Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_vid_brand_recommend_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b7", "return_n_uv", b7Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_vid_hotsencetype_recommend_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b8", "return_n_uv", b8Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_merge_cate1_recommend_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b9", "return_n_uv", b9Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_merge_cate2_recommend_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b10", "return_n_uv", b10Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_channel_recommend_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b11", "return_n_uv", b11Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_festive_recommend_exp_feature_20250212"), featMap);
+        oneTypeStatFeature("b13", "return_n_uv", b13Periods, videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_video_unionid_recommend_exp_feature_20250212"), featMap);
+
+        // head video cf
+        headVideoCFD1Feature("d1", videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("scene_type_vid_cf_feature_20250212"), featMap);
+        headVideoCFD2Feature("d2", videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("vid_click_cf_feature_20250212"), featMap);
+        headVideoCFD3Feature("d3", videoOriginInfo.getOrDefault(vid, new HashMap<>()).get("alg_recsys_feature_cf_i2i_v2"), featMap);
+    }
+
+    public static void getVideoBaseFeature(String prefix, long currentMs, Map<String, String> videoInfo, Map<String, Double> featMap) {
+        if (null == videoInfo || videoInfo.isEmpty()) {
+            return;
+        }
+        featMap.put(prefix + "@total_time", FeatureUtils.log1(Double.parseDouble(videoInfo.getOrDefault("total_time", "0")), log1Scale));
+        featMap.put(prefix + "@bit_rate", FeatureUtils.log1(Double.parseDouble(videoInfo.getOrDefault("bit_rate", "0")), log1Scale));
+        if (videoInfo.containsKey("width") && videoInfo.containsKey("height")) {
+            String resolution = String.format("%s@%s@%s_%s", prefix, "wh", videoInfo.get("width"), videoInfo.get("height"));
+            featMap.put(resolution, 1.0);
+        }
+
+        // cate
+        getVideoCateFeature(prefix, videoInfo, featMap);
+        if (videoInfo.containsKey("title")) {
+            int id = FeatureUtils.judgeVideoTimeType(videoInfo.get("title"));
+            if (id > 0) {
+                String key = String.format("%s@%s@%d", prefix, "tt", id);
+                featMap.put(key, 1.0);
+            }
+        }
+
+        // time
+        try {
+            if (videoInfo.containsKey("gmt_create_timestamp")) {
+                String createMsStr = videoInfo.get("gmt_create_timestamp");
+                long createMs = Long.parseLong(createMsStr);
+                double createTime = FeatureUtils.getTimeDiff(currentMs, createMs);
+                featMap.put(prefix + "@ts", 1 - createTime);
+            }
+        } catch (Exception ignored) {
+        }
+    }
+
+    public static void getHeadRankVideoCrossFeature(Map<String, String> headInfo, Map<String, String> rankInfo, Map<String, Double> featMap) {
+        getTwoVideoCrossFeature("hr_sim", videoSimAttrs, headInfo, rankInfo, featMap);
+    }
+
+    public static void getProfileVideoCrossFeature(long currentMs, UserShareReturnProfile profile, Map<String, String> rankVideo, Map<String, Map<String, String>> hVideoMap, Map<String, Double> featMap) {
+        if (null == profile) {
+            return;
+        }
+        getRSCrossFeature("c9_mss", currentMs, seqMaxN, profile.getM_s_s(), rankVideo, hVideoMap, featMap);
+        getRSCrossFeature("c9_mrs", currentMs, seqMaxN, profile.getM_r_s(), rankVideo, hVideoMap, featMap);
+        getRSCrossFeature("c9_lss", currentMs, seqLastN, profile.getL_s_s(), rankVideo, hVideoMap, featMap);
+        getRSCrossFeature("c9_lrs", currentMs, seqLastN, profile.getL_r_s(), rankVideo, hVideoMap, featMap);
+
+        if (null == rankVideo || rankVideo.isEmpty()) {
+            return;
+        }
+        getVideoAttrSRCrossFeature("c9_c1s", rankVideo.getOrDefault("merge_first_level_cate", ""), profile.getC1_s(), featMap);
+        getVideoAttrSRCrossFeature("c9_c2s", rankVideo.getOrDefault("merge_second_level_cate", ""), profile.getC2_s(), featMap);
+        getVideoAttrSRCrossFeature("c9_l1s", rankVideo.getOrDefault("festive_label1", ""), profile.getL1_s(), featMap);
+        getVideoAttrSRCrossFeature("c9_l2s", rankVideo.getOrDefault("festive_label2", ""), profile.getL2_s(), featMap);
+    }
+
+    private static void getRSCrossFeature(String prefix, long currentMs, int maxN, List<UserSRBO> list, Map<String, String> rankVideo, Map<String, Map<String, String>> hVideoMap, Map<String, Double> featMap) {
+        if (null != list && !list.isEmpty()) {
+            for (int i = 0; i < list.size() && i < maxN; i++) {
+                UserSRBO u = list.get(i);
+                if (null != u) {
+                    long id = u.getId();
+                    long cnt = u.getCnt();
+                    long uv = u.getUv();
+                    long ts = u.getTs();
+                    if (id > 0) {
+                        String vid = id + "";
+                        String baseKey = String.format("%s@%d", prefix, i + 1);
+                        if (cnt > 0) {
+                            featMap.put(baseKey + "@cnt", FeatureUtils.log1(cnt, log1Scale));
+                        }
+                        if (uv > 0) {
+                            featMap.put(baseKey + "@uv", FeatureUtils.log1(uv, log1Scale));
+                        }
+                        if (ts > 0) {
+                            long historyMs = ts * 1000;
+                            featMap.put(baseKey + "@ts", 1 - FeatureUtils.getTimeDiff(currentMs, historyMs));
+
+                            // history week & hour
+                            Calendar calendar = Calendar.getInstance();
+                            calendar.setTimeInMillis(historyMs);
+                            featMap.put(String.format("%s_week@%d", baseKey, calendar.get(Calendar.DAY_OF_WEEK)), 1.0);
+                            featMap.put(String.format("%s_hour@%d", baseKey, calendar.get(Calendar.HOUR_OF_DAY) + 1), 1.0);
+                        }
+                        if (null != hVideoMap && hVideoMap.containsKey(vid)) {
+                            Map<String, String> hVideo = hVideoMap.get(vid);
+                            //getVideoCateFeature(baseKey, hVideo, featMap);
+                            getTwoVideoCrossFeature(baseKey, hVideoSimAttrs, hVideo, rankVideo, featMap);
+                        }
+                    }
+                }
+            }
+        }
+    }
+
+    private static void getVideoAttrSRCrossFeature(String prefix, String attr, Map<String, VideoAttrSRBO> attrMap, Map<String, Double> featMap) {
+        if (null == attrMap || attrMap.isEmpty()) {
+            return;
+        }
+        attr = attr.trim();
+        if (attrMap.containsKey(attr)) {
+            VideoAttrSRBO bo = attrMap.get(attr);
+            if (null != bo) {
+                long sp = bo.getSp();    // share_pv
+                long rp = bo.getRp();    // return_n_pv_noself
+                long ru = bo.getRu();    // return_n_uv_noself
+                long mu = bo.getMu();    // max_return_uv
+                if (sp > 0) {
+                    double sp_s = FeatureUtils.log1(sp, log1Scale);
+                    double rp_s = FeatureUtils.log1(rp, log1Scale);
+                    double ru_s = FeatureUtils.log1(ru, log1Scale);
+                    double mu_s = FeatureUtils.log1(mu, log1Scale);
+
+                    double ros_one = FeatureUtils.wilsonScore(rp, sp);
+                    double ros = FeatureUtils.plusSmooth(ru, sp, smoothPlus);
+                    double ros_minus = FeatureUtils.plusSmooth(ru, rp, smoothPlus);
+
+                    featMap.put(prefix + "@sp", sp_s);
+                    featMap.put(prefix + "@rp", rp_s);
+                    featMap.put(prefix + "@ru", ru_s);
+                    featMap.put(prefix + "@mu", mu_s);
+                    featMap.put(prefix + "@ros_one", ros_one);
+                    featMap.put(prefix + "@ros", ros);
+                    featMap.put(prefix + "@ros_minus", ros_minus);
+                }
+            }
+        }
+    }
+
+    private static void getVideoCateFeature(String prefix, Map<String, String> videoInfo, Map<String, Double> featMap) {
+        if (null == videoInfo || videoInfo.isEmpty()) {
+            return;
+        }
+        for (String attr : videoCateAttrs) {
+            String attrVal = videoInfo.getOrDefault(attr, "");
+            attrVal = attrVal.trim();
+            if (!attrVal.isEmpty()) {
+                String key = String.format("%s@%s@%s", prefix, attr, attrVal);
+                featMap.put(key, 1.0);
+            }
+        }
+        if (videoInfo.containsKey("keywords")) {
+            String keywords = videoInfo.get("keywords");
+            if (null != keywords && !keywords.isEmpty()) {
+                for (String kw : keywords.split(",")) {
+                    kw = kw.replaceAll("(\\s+|\\t|:)", "");
+                    if (!kw.isEmpty()) {
+                        String featKey = String.format("%s@kw@%s", prefix, kw);
+                        featMap.put(featKey, 1.0);
+                    }
+                }
+            }
+        }
+    }
+
+    private static void getTwoVideoCrossFeature(String prefix, List<String> attrs, Map<String, String> video1, Map<String, String> video2, Map<String, Double> featMap) {
+        if (null == video1 || video1.isEmpty() || null == video2 || video2.isEmpty()) {
+            return;
+        }
+        for (String attr : attrs) {
+            String attr1 = video1.getOrDefault(attr, "");
+            String attr2 = video2.getOrDefault(attr, "");
+            if (!"".equals(attr1) && !"unknown".equals(attr1) && !"".equals(attr2) && !"unknown".equals(attr2)) {
+                double simScore = SimilarityUtils.word2VecSimilarity(attr1, attr2);
+                featMap.put(prefix + "@" + attr, simScore);
+            }
+        }
+    }
+
+    private static void headVideoCFD1Feature(String prefix, Map<String, String> infoMap, Map<String, Double> featMap) {
+        double ros_cf_score = getOneInfo("ros_cf_score", infoMap);
+        double ros_cf_rank = getOneInfo("ros_cf_rank", infoMap);
+        double rov_cf_score = getOneInfo("rov_cf_score", infoMap);
+        double rov_cf_rank = getOneInfo("rov_cf_rank", infoMap);
+        featMap.put(prefix + "@ros_cf_score", ros_cf_score);
+        featMap.put(prefix + "@ros_cf_rank", ros_cf_rank);
+        featMap.put(prefix + "@rov_cf_score", rov_cf_score);
+        featMap.put(prefix + "@rov_cf_rank", rov_cf_rank);
+    }
+
+    private static void headVideoCFD2Feature(String prefix, Map<String, String> infoMap, Map<String, Double> featMap) {
+        double score = getOneInfo("score", infoMap);
+        double rank = getOneInfo("rank", infoMap);
+        featMap.put(prefix + "@score", score);
+        featMap.put(prefix + "@rank", rank);
+    }
+
+    private static void headVideoCFD3Feature(String prefix, Map<String, String> infoMap, Map<String, Double> featMap) {
+        double exp = getOneInfo("exp", infoMap);
+        double return_n = getOneInfo("return_n", infoMap);
+        double rovn = FeatureUtils.plusSmooth(return_n, exp, smoothPlus);
+        featMap.put(prefix + "@exp", FeatureUtils.log1(exp, log1Scale));
+        featMap.put(prefix + "@return_n", FeatureUtils.log1(return_n, log1Scale));
+        featMap.put(prefix + "@rovn", rovn);
+    }
+
+    public static Map<String, Map<String, String[]>> parseUCFScore(Map<String, String> mapInfo) {
+        Map<String, Map<String, String[]>> allScoresMap = new HashMap<>();
+        for (String cfType : cfList) {
+            String data = mapInfo.getOrDefault(cfType, "");
+            if (!data.isEmpty()) {
+                Map<String, String[]> oneScoresMap = new HashMap<>();
+                String[] entries = data.split(",");
+                for (String entry : entries) {
+                    String[] rList = entry.split(":");
+                    if (rList.length >= 4) { // 确保分割后有四个元素
+                        String key = rList[0];
+                        String value1 = rList[1];
+                        String value2 = rList[2];
+                        String value3 = rList[3];
+                        String[] strs = {value1, value2, value3};
+                        oneScoresMap.put(key, strs);
+                    }
+                }
+                if (!oneScoresMap.isEmpty()) {
+                    allScoresMap.put(cfType, oneScoresMap);
+                }
+            }
+        }
+        return allScoresMap;
+    }
+
+    private static void getRateStatFeature(String prefix, String calType, List<String> periods, Map<String, String> infoMap, Map<String, Double> featMap) {
+        if (null == infoMap || infoMap.isEmpty()) {
+            return;
+        }
+        for (String period : periods) {
+            double str_one = getOneInfo(calType + "str_one_" + period, infoMap);
+            double ros_one = getOneInfo(calType + "ros_one_" + period, infoMap);
+            double str = getOneInfo(calType + "str_" + period, infoMap);
+            double ros = getOneInfo(calType + "ros_" + period, infoMap);
+            double str_plus = getOneInfo(calType + "str_plus_" + period, infoMap);
+            double ros_minus = getOneInfo(calType + "ros_minus_" + period, infoMap);
+            double rovn = getOneInfo(calType + "rovn_" + period, infoMap);
+
+            featMap.put(prefix + "_" + period + "@" + calType + "str_one", str_one);
+            featMap.put(prefix + "_" + period + "@" + calType + "ros_one", ros_one);
+            featMap.put(prefix + "_" + period + "@" + calType + "str", str);
+            featMap.put(prefix + "_" + period + "@" + calType + "ros", ros);
+            featMap.put(prefix + "_" + period + "@" + calType + "str_plus", str_plus);
+            featMap.put(prefix + "_" + period + "@" + calType + "ros_minus", ros_minus);
+            featMap.put(prefix + "_" + period + "@" + calType + "rovn", rovn);
+        }
+    }
+
+    private static void oneTypeStatFeature(String prefix, String uvPrefix, List<String> periods, Map<String, String> infoMap, Map<String, Double> featMap) {
+        if (null == infoMap || infoMap.isEmpty()) {
+            return;
+        }
+        for (String period : periods) {
+            double exp = getOneInfo("exp_" + period, infoMap);
+            if (!FeatureUtils.greaterThanZero(exp)) {
+                continue;
+            }
+            double is_share = getOneInfo("is_share_" + period, infoMap);
+            double share_cnt = getOneInfo("share_cnt_" + period, infoMap);
+            double is_return_1 = getOneInfo("is_return_1_" + period, infoMap);
+            double return_n_uv = getOneInfo(uvPrefix + "_" + period, infoMap);
+
+            double exp_s = FeatureUtils.log1(exp, log1Scale);
+            double is_share_s = FeatureUtils.log1(is_share, log1Scale);
+            double share_cnt_s = FeatureUtils.log1(share_cnt, log1Scale);
+            double is_return_1_s = FeatureUtils.log1(is_return_1, log1Scale);
+            double return_n_uv_s = FeatureUtils.log1(return_n_uv, log1Scale);
+
+            double str = FeatureUtils.wilsonScore(is_share, exp);
+            double str_plus = FeatureUtils.wilsonScore(is_return_1, exp);
+            double ros_one = FeatureUtils.wilsonScore(is_return_1, is_share);
+
+            double rovn = FeatureUtils.plusSmooth(return_n_uv, exp, smoothPlus);
+            double ros = FeatureUtils.plusSmooth(return_n_uv, is_share, smoothPlus);
+            double ros_n = FeatureUtils.plusSmooth(return_n_uv, share_cnt, smoothPlus);
+            double ros_minus = FeatureUtils.plusSmooth(return_n_uv, is_return_1, smoothPlus);
+
+            featMap.put(prefix + "_" + period + "@" + "exp", exp_s);
+            featMap.put(prefix + "_" + period + "@" + "is_share", is_share_s);
+            featMap.put(prefix + "_" + period + "@" + "share_cnt", share_cnt_s);
+            featMap.put(prefix + "_" + period + "@" + "is_return_1", is_return_1_s);
+            featMap.put(prefix + "_" + period + "@" + "return_n_uv", return_n_uv_s);
+            featMap.put(prefix + "_" + period + "@" + "str", str);
+            featMap.put(prefix + "_" + period + "@" + "str_plus", str_plus);
+            featMap.put(prefix + "_" + period + "@" + "ros_one", ros_one);
+            featMap.put(prefix + "_" + period + "@" + "rovn", rovn);
+            featMap.put(prefix + "_" + period + "@" + "ros", ros);
+            featMap.put(prefix + "_" + period + "@" + "ros_n", ros_n);
+            featMap.put(prefix + "_" + period + "@" + "ros_minus", ros_minus);
+        }
+    }
+
+    private static void oneTypeStatFeature(String prefix, List<String> periods, Map<String, String> infoMap, Map<String, Double> featMap) {
+        if (null == infoMap || infoMap.isEmpty()) {
+            return;
+        }
+        for (String period : periods) {
+            double exp = getOneInfo("exp_" + period, infoMap);
+            if (!FeatureUtils.greaterThanZero(exp)) {
+                continue;
+            }
+            double is_share = getOneInfo("is_share_" + period, infoMap);
+            double share_cnt = getOneInfo("share_cnt_" + period, infoMap);
+            double is_return_1 = getOneInfo("is_return_1_" + period, infoMap);
+            double return_1_uv = getOneInfo("return_1_uv_" + period, infoMap);
+            double return_n_uv = getOneInfo("return_n_uv_" + period, infoMap);
+
+            double exp_s = FeatureUtils.log1(exp, log1Scale);
+            double is_share_s = FeatureUtils.log1(is_share, log1Scale);
+            double share_cnt_s = FeatureUtils.log1(share_cnt, log1Scale);
+            double is_return_1_s = FeatureUtils.log1(is_return_1, log1Scale);
+            double return_1_uv_s = FeatureUtils.log1(return_1_uv, log1Scale);
+            double return_n_uv_s = FeatureUtils.log1(return_n_uv, log1Scale);
+
+            double str = FeatureUtils.wilsonScore(is_share, exp);
+            double str_plus = FeatureUtils.wilsonScore(is_return_1, exp);
+            double ros_one = FeatureUtils.wilsonScore(is_return_1, is_share);
+
+            double rovn1 = FeatureUtils.plusSmooth(return_1_uv, exp, smoothPlus);
+            double ros1 = FeatureUtils.plusSmooth(return_1_uv, is_share, smoothPlus);
+            double ros_n1 = FeatureUtils.plusSmooth(return_1_uv, share_cnt, smoothPlus);
+            double ros_minus1 = FeatureUtils.plusSmooth(return_1_uv, is_return_1, smoothPlus);
+
+            double rovn = FeatureUtils.plusSmooth(return_n_uv, exp, smoothPlus);
+            double ros = FeatureUtils.plusSmooth(return_n_uv, is_share, smoothPlus);
+            double ros_n = FeatureUtils.plusSmooth(return_n_uv, share_cnt, smoothPlus);
+            double ros_minus = FeatureUtils.plusSmooth(return_n_uv, is_return_1, smoothPlus);
+
+            featMap.put(prefix + "_" + period + "@" + "exp", exp_s);
+            featMap.put(prefix + "_" + period + "@" + "is_share", is_share_s);
+            featMap.put(prefix + "_" + period + "@" + "share_cnt", share_cnt_s);
+            featMap.put(prefix + "_" + period + "@" + "is_return_1", is_return_1_s);
+            featMap.put(prefix + "_" + period + "@" + "return_1_uv", return_1_uv_s);
+            featMap.put(prefix + "_" + period + "@" + "return_n_uv", return_n_uv_s);
+            featMap.put(prefix + "_" + period + "@" + "str", str);
+            featMap.put(prefix + "_" + period + "@" + "str_plus", str_plus);
+            featMap.put(prefix + "_" + period + "@" + "ros_one", ros_one);
+            featMap.put(prefix + "_" + period + "@" + "rovn1", rovn1);
+            featMap.put(prefix + "_" + period + "@" + "ros1", ros1);
+            featMap.put(prefix + "_" + period + "@" + "ros_n1", ros_n1);
+            featMap.put(prefix + "_" + period + "@" + "ros_minus1", ros_minus1);
+            featMap.put(prefix + "_" + period + "@" + "rovn", rovn);
+            featMap.put(prefix + "_" + period + "@" + "ros", ros);
+            featMap.put(prefix + "_" + period + "@" + "ros_n", ros_n);
+            featMap.put(prefix + "_" + period + "@" + "ros_minus", ros_minus);
+        }
+    }
+
+    private static double getOneInfo(String name, Map<String, String> map) {
+        if (null == map) {
+            return 0.0;
+        }
+        return map.isEmpty() ? 0 : Double.parseDouble(map.getOrDefault(name, "0.0"));
+    }
+}

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/recall/RecallParam.java

@@ -32,5 +32,6 @@ public class RecallParam {
 
     private boolean riskUser;
     private String rootSourceId;
+    private Integer userShareDepth;
 
 }

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/recall/RecallService.java

@@ -20,6 +20,8 @@ import java.util.concurrent.CountDownLatch;
 import java.util.concurrent.ExecutorService;
 import java.util.concurrent.Future;
 import java.util.concurrent.TimeUnit;
+import java.util.regex.Matcher;
+import java.util.stream.Collectors;
 
 /**
  * @author dyp
@@ -110,21 +112,19 @@ public class RecallService implements ApplicationContextAware {
         strategies.add(strategyMap.get(SceneCFRovnRecallStrategy.class.getSimpleName()));
         strategies.add(strategyMap.get(SceneCFRosnRecallStrategy.class.getSimpleName()));
         Set<String> abExpCodes = param.getAbExpCodes();
-        if (CollectionUtils.isNotEmpty(abExpCodes) && abExpCodes.contains("568")) {
-            // strategies.remove(strategyMap.get(ReturnVideoRecallStrategy.class.getSimpleName()));
-            strategies.add(strategyMap.get(RegionRealtimeRecallStrategyV7LongTermV1.class.getSimpleName()));
-            strategies.add(strategyMap.get(RegionRealtimeRecallStrategyROS.class.getSimpleName()));
-        }
         if (CollectionUtils.isNotEmpty(abExpCodes) && abExpCodes.contains("567")) {
             strategies.add(strategyMap.get(UserCate1RecallStrategy.class.getSimpleName()));
             strategies.add(strategyMap.get(UserCate2RecallStrategy.class.getSimpleName()));
             strategies.add(strategyMap.get(HeadProvinceCate1RecallStrategy.class.getSimpleName()));
             strategies.add(strategyMap.get(HeadProvinceCate2RecallStrategy.class.getSimpleName()));
         }
-        if (CollectionUtils.isNotEmpty(abExpCodes) && abExpCodes.contains("568") && FeatureUtils.lowFissionChannel(param.getRootSourceId())) {
-            strategies.add(strategyMap.get(HeadCate1STRRecallStrategy.class.getSimpleName()));
-            strategies.add(strategyMap.get(HeadCate2STRRecallStrategy.class.getSimpleName()));
-            strategies.add(strategyMap.get(ProvinceSTRRecallStrategy.class.getSimpleName()));
+        if (CollectionUtils.isNotEmpty(abExpCodes) && abExpCodes.contains("568")) {
+            Matcher matcher = FeatureUtils.getChannelMatcher(param.getRootSourceId());
+            if (null != matcher && matcher.find() && FeatureUtils.firstLevel(param.getUserShareDepth())) {
+                strategies.add(strategyMap.get(ChannelROVRecallStrategy.class.getSimpleName()));
+                Set<String> filterRecallSet = new HashSet<>(Arrays.asList(RegionRealtimeRecallStrategyV1.PUSH_FORM, SceneCFRovnRecallStrategy.PUSH_FORM, SceneCFRosnRecallStrategy.PUSH_FORM));
+                strategies = strategies.stream().filter(r -> !filterRecallSet.contains(r.pushFrom())).collect(Collectors.toList());
+            }
         }
 
         // 命中用户黑名单不走流量池

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/recall/strategy/ChannelROVRecallStrategy.java

@@ -0,0 +1,134 @@
+package com.tzld.piaoquan.recommend.server.service.recall.strategy;
+
+import com.tzld.piaoquan.recommend.server.model.Video;
+import com.tzld.piaoquan.recommend.server.service.filter.FilterParam;
+import com.tzld.piaoquan.recommend.server.service.filter.FilterResult;
+import com.tzld.piaoquan.recommend.server.service.filter.FilterService;
+import com.tzld.piaoquan.recommend.server.service.recall.FilterParamFactory;
+import com.tzld.piaoquan.recommend.server.service.recall.RecallParam;
+import com.tzld.piaoquan.recommend.server.service.recall.RecallStrategy;
+import com.tzld.piaoquan.recommend.server.util.FeatureUtils;
+import lombok.extern.slf4j.Slf4j;
+import org.apache.commons.collections4.CollectionUtils;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.beans.factory.annotation.Qualifier;
+import org.springframework.data.redis.core.RedisTemplate;
+import org.springframework.stereotype.Component;
+
+import java.util.*;
+import java.util.regex.Matcher;
+import java.util.stream.Collectors;
+
+@Component
+@Slf4j
+public class ChannelROVRecallStrategy implements RecallStrategy {
+    private final String CLASS_NAME = this.getClass().getSimpleName();
+    @Autowired
+    private FilterService filterService;
+    @Autowired
+    @Qualifier("redisTemplate")
+    public RedisTemplate<String, String> redisTemplate;
+
+    public static final String channelGroupPrefix = "alg_recsys_user_channel_group";
+
+    public static final String PUSH_FORM = "recall_strategy_channel_rovn";
+    public static final String redisKeyPrefix = "channel_rovn_recall";
+
+    @Override
+    public String pushFrom() {
+        return PUSH_FORM;
+    }
+
+    @Override
+    public List<Video> recall(RecallParam param) {
+        List<Video> videosResult = new ArrayList<>();
+        try {
+            if (!FeatureUtils.firstLevel(param.getUserShareDepth())) {
+                return videosResult;
+            }
+
+            String channelName = getChannelName(param.getRootSourceId());
+            if (channelName.isEmpty()) {
+                return videosResult;
+            }
+
+            String key = String.format("%s:%s", redisKeyPrefix, channelName);
+            String value = redisTemplate.opsForValue().get(key);
+            if (null == value || value.isEmpty()) {
+                return videosResult;
+            }
+            List<Long> vidList = parseVidList(param.getVideoId(), value);
+            fillVideoResult(param, vidList, videosResult);
+        } catch (Exception e) {
+            log.error("recall is wrong in {}, error={}", CLASS_NAME, e);
+        }
+        return videosResult;
+    }
+
+    private List<Long> parseVidList(Long headVid, String data) {
+        List<Long> vidList = new ArrayList<>();
+        if (null != data && !data.isEmpty()) {
+            String[] pair = data.split("\t");
+            if (2 == pair.length) {
+                Set<Long> hit = new HashSet<>();
+                hit.add(headVid);
+                List<Long> ids = Arrays.stream(pair[0].split(",")).map(Long::valueOf).collect(Collectors.toList());
+                if (!ids.isEmpty()) {
+                    for (Long id : ids) {
+                        if (!hit.contains(id)) {
+                            hit.add(id);
+                            vidList.add(id);
+                        }
+                    }
+                }
+            }
+        }
+        return vidList;
+    }
+
+    private void fillVideoResult(RecallParam param, List<Long> vidList, List<Video> videosResult) {
+        FilterParam filterParam = FilterParamFactory.create(param, vidList);
+        FilterResult filterResult = filterService.filter(filterParam);
+        if (filterResult != null && CollectionUtils.isNotEmpty(filterResult.getVideoIds())) {
+            List<Long> filterIds = filterResult.getVideoIds();
+            int n = filterIds.size();
+            for (int i = 0; i < n; i++) {
+                Video video = new Video();
+                video.setVideoId(filterIds.get(i));
+                video.setRovScore(n - i);
+                video.setPushFrom(pushFrom());
+                videosResult.add(video);
+            }
+        }
+    }
+
+    private String getChannelName(String s) {
+        Matcher matcher = FeatureUtils.getChannelMatcher(s);
+        if (null != matcher && matcher.find()) {
+            switch (matcher.group(0)) {
+                case "longArticles_":
+                    return getChannelType(s);
+                case "dyyjs_":
+                    return "公众号代运营-即转";
+                case "touliu_tencent_":
+                    return "小程序投流";
+                case "touliu_tencentgzh_":
+                case "touliu_tencentGzhArticle_":
+                case "GzhTouLiu_Articles_gh":
+                    return "公众号投流";
+                default:
+                    return "";
+            }
+        }
+        return "";
+    }
+
+    private String getChannelType(String s) {
+        String key = String.format("%s:%s", channelGroupPrefix, s);
+        String value = redisTemplate.opsForValue().get(key);
+        if (null != value && value.equals("公众号买号")) {
+            return value;
+        }
+        return "公众号代运营-Daily";
+    }
+}

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/score/ScorerUtils.java

@@ -33,14 +33,11 @@ public final class ScorerUtils {
         ScorerUtils.init(VIDEO_SCORE_CONF_FOR_AD);
         ScorerUtils.init("feeds_score_config_20240609.conf");
         ScorerUtils.init("feeds_score_config_20240807.conf");
-        ScorerUtils.init("feeds_score_config_fm_xgb_20250221.conf");
         ScorerUtils.init("feeds_score_config_fm_xgb_20250303.conf");
-        ScorerUtils.init("feeds_score_config_xgb_20241209.conf");
-        ScorerUtils.init("feeds_score_config_xgb_20250109.conf");
-        ScorerUtils.init("feeds_score_config_xgb_rov_20241209.conf");
-        ScorerUtils.init("feeds_score_config_xgb_rov_20250109.conf");
+        ScorerUtils.init("feeds_score_config_fm_xgb_20250317.conf");
         ScorerUtils.init("feeds_score_config_xgb_str_20250228.conf");
         ScorerUtils.init("feeds_score_config_xgb_ros_20250311.conf");
+        ScorerUtils.init("feeds_score_config_xgb_ros_binary_20250319.conf");
         ScorerUtils.init4Recall("feeds_recall_config_region_v1.conf");
         ScorerUtils.init4Recall("feeds_recall_config_region_ros.conf");
         ScorerUtils.init4Recall("feeds_score_config_bless.conf");

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/util/FeatureUtils.java

@@ -9,6 +9,7 @@ public class FeatureUtils {
     public static final String cate1Attr = "cate1_list";
     public static final String cate2Attr = "cate2";
     public static final String festive1Attr = "festive_label1";
+    public static final String channelAttr = "channel";
     private static final Map<String, Integer> cate1MAP = new HashMap<>();
     private static final Map<String, Integer> cate2MAP = new HashMap<>();
     private static final Map<String, Integer> festive1Map = new HashMap<>();
@@ -17,11 +18,12 @@ public class FeatureUtils {
     private static final String goodMorningRegex = "(早安|早上好|早晨好|上午好)";
     private static final String goodAfternoonRegex = "(午安|中午好|下午好)";
     private static final String goodEveningRegex = "(晚安|晚上好)";
-    private static final String lowFissionChannelRegex = "(longArticles_|dyyjs_|daitou_tencentgzh|DaiTou_gh)";
+    //private static final String channelRegex = "(longArticles_|dyyjs_|touliu_tencent_|touliu_tencentgzh_|touliu_tencentGzhArticle_|GzhTouLiu_Articles_gh)";
+    private static final String channelRegex = "(dyyjs_|touliu_tencent_)";
     private static final Pattern goodMorningPattern = Pattern.compile(goodMorningRegex);
     private static final Pattern goodAfternoonPattern = Pattern.compile(goodAfternoonRegex);
     private static final Pattern goodEveningPattern = Pattern.compile(goodEveningRegex);
-    private static final Pattern lowFissionChannelPattern = Pattern.compile(lowFissionChannelRegex);
+    private static final Pattern channelPattern = Pattern.compile(channelRegex);
 
     static {
         cate1MAP.put("情感", 1);
@@ -121,6 +123,13 @@ public class FeatureUtils {
         return Math.log(data + 1.0);
     }
 
+    public static double log1(double data, double scale) {
+        if (data <= 0) {
+            return 0D;
+        }
+        return Math.log(data + 1.0) / scale;
+    }
+
     public static double plusSmooth(double a, double b, double plus) {
         if (a == 0 || b == 0) {
             return 0D;
@@ -149,11 +158,14 @@ public class FeatureUtils {
         return value > 1E-8;
     }
 
-    public static boolean lowFissionChannel(String s) {
+    public static boolean firstLevel(Integer userShareDepth) {
+        return null != userShareDepth && 0 == userShareDepth;
+    }
+
+    public static Matcher getChannelMatcher(String s) {
         if (null != s && !s.isEmpty()) {
-            Matcher morning = lowFissionChannelPattern.matcher(s);
-            return morning.find();
+            return channelPattern.matcher(s);
         }
-        return false;
+        return null;
     }
 }

recommend-server-service/src/main/resources/feeds_score_config_fm_xgb_20250317.conf

@@ -0,0 +1,467 @@
+scorer-config = {
+  rov-score-config = {
+     scorer-name = "com.tzld.piaoquan.recommend.server.service.score.VlogRovFMScorer"
+     scorer-priority = 96
+     model-path = "zhangbo/model_fm_for_recsys_v6_rov.txt"
+  }
+  nor-score-config = {
+    scorer-name = "com.tzld.piaoquan.recommend.server.service.score.NorXGBRegressionScorer"
+    scorer-priority = 97
+    model-path = "zhangbo/model_xgb_for_recsys_v6_nor.tar.gz"
+    param = {
+      localDir = "xgboost/recsys_v6_nor"
+      features = [
+      "b0_12h@exp",
+      "b0_12h@is_return_1",
+      "b0_12h@is_share",
+      "b0_12h@return_1_uv",
+      "b0_12h@return_n_uv",
+      "b0_12h@ros",
+      "b0_12h@ros1",
+      "b0_12h@ros_minus",
+      "b0_12h@ros_minus1",
+      "b0_12h@ros_n",
+      "b0_12h@ros_n1",
+      "b0_12h@ros_one",
+      "b0_12h@rovn",
+      "b0_12h@rovn1",
+      "b0_12h@share_cnt",
+      "b0_12h@str",
+      "b0_12h@str_plus",
+      "b0_1h@exp",
+      "b0_1h@is_return_1",
+      "b0_1h@is_share",
+      "b0_1h@return_1_uv",
+      "b0_1h@return_n_uv",
+      "b0_1h@ros",
+      "b0_1h@ros1",
+      "b0_1h@ros_minus",
+      "b0_1h@ros_minus1",
+      "b0_1h@ros_n",
+      "b0_1h@ros_n1",
+      "b0_1h@ros_one",
+      "b0_1h@rovn",
+      "b0_1h@rovn1",
+      "b0_1h@share_cnt",
+      "b0_1h@str",
+      "b0_1h@str_plus",
+      "b0_3h@exp",
+      "b0_3h@is_return_1",
+      "b0_3h@is_share",
+      "b0_3h@return_1_uv",
+      "b0_3h@return_n_uv",
+      "b0_3h@ros",
+      "b0_3h@ros1",
+      "b0_3h@ros_minus",
+      "b0_3h@ros_minus1",
+      "b0_3h@ros_n",
+      "b0_3h@ros_n1",
+      "b0_3h@ros_one",
+      "b0_3h@rovn",
+      "b0_3h@rovn1",
+      "b0_3h@share_cnt",
+      "b0_3h@str",
+      "b0_3h@str_plus",
+      "b0_6h@exp",
+      "b0_6h@is_return_1",
+      "b0_6h@is_share",
+      "b0_6h@return_1_uv",
+      "b0_6h@return_n_uv",
+      "b0_6h@ros",
+      "b0_6h@ros1",
+      "b0_6h@ros_minus",
+      "b0_6h@ros_minus1",
+      "b0_6h@ros_n",
+      "b0_6h@ros_n1",
+      "b0_6h@ros_one",
+      "b0_6h@rovn",
+      "b0_6h@rovn1",
+      "b0_6h@share_cnt",
+      "b0_6h@str",
+      "b0_6h@str_plus",
+      "b10_12h@is_share",
+      "b10_12h@return_n_uv",
+      "b10_12h@ros",
+      "b10_12h@ros_minus",
+      "b10_12h@rovn",
+      "b10_12h@str",
+      "b10_12h@str_plus",
+      "b10_1h@is_share",
+      "b10_1h@return_n_uv",
+      "b10_1h@ros",
+      "b10_1h@ros_minus",
+      "b10_1h@rovn",
+      "b10_1h@str",
+      "b10_1h@str_plus",
+      "b11_12h@is_share",
+      "b11_12h@return_n_uv",
+      "b11_12h@ros",
+      "b11_12h@ros_minus",
+      "b11_12h@rovn",
+      "b11_12h@str",
+      "b11_12h@str_plus",
+      "b11_168h@is_share",
+      "b11_168h@return_n_uv",
+      "b11_168h@ros",
+      "b11_168h@ros_minus",
+      "b11_168h@rovn",
+      "b11_168h@str",
+      "b11_168h@str_plus",
+      "b13_168h@is_share",
+      "b13_168h@return_n_uv",
+      "b13_168h@ros",
+      "b13_168h@ros_minus",
+      "b13_168h@ros_n",
+      "b13_168h@ros_one",
+      "b13_168h@rovn",
+      "b13_168h@str",
+      "b13_168h@str_plus",
+      "b13_24h@is_share",
+      "b13_24h@return_n_uv",
+      "b13_24h@ros",
+      "b13_24h@ros_minus",
+      "b13_24h@ros_n",
+      "b13_24h@ros_one",
+      "b13_24h@rovn",
+      "b13_24h@str",
+      "b13_24h@str_plus",
+      "b1_168h@exp",
+      "b1_168h@is_return_1",
+      "b1_168h@is_share",
+      "b1_168h@return_n_uv",
+      "b1_168h@ros",
+      "b1_168h@ros_minus",
+      "b1_168h@ros_n",
+      "b1_168h@ros_one",
+      "b1_168h@rovn",
+      "b1_168h@share_cnt",
+      "b1_168h@str",
+      "b1_168h@str_plus",
+      "b1_1h@exp",
+      "b1_1h@is_return_1",
+      "b1_1h@is_share",
+      "b1_1h@return_n_uv",
+      "b1_1h@ros",
+      "b1_1h@ros_minus",
+      "b1_1h@ros_n",
+      "b1_1h@ros_one",
+      "b1_1h@rovn",
+      "b1_1h@share_cnt",
+      "b1_1h@str",
+      "b1_1h@str_plus",
+      "b1_24h@exp",
+      "b1_24h@is_return_1",
+      "b1_24h@is_share",
+      "b1_24h@return_n_uv",
+      "b1_24h@ros",
+      "b1_24h@ros_minus",
+      "b1_24h@ros_n",
+      "b1_24h@ros_one",
+      "b1_24h@rovn",
+      "b1_24h@share_cnt",
+      "b1_24h@str",
+      "b1_24h@str_plus",
+      "b1_3h@exp",
+      "b1_3h@is_return_1",
+      "b1_3h@is_share",
+      "b1_3h@return_n_uv",
+      "b1_3h@ros",
+      "b1_3h@ros_minus",
+      "b1_3h@ros_n",
+      "b1_3h@ros_one",
+      "b1_3h@rovn",
+      "b1_3h@share_cnt",
+      "b1_3h@str",
+      "b1_3h@str_plus",
+      "b1_72h@exp",
+      "b1_72h@is_return_1",
+      "b1_72h@is_share",
+      "b1_72h@return_n_uv",
+      "b1_72h@ros",
+      "b1_72h@ros_minus",
+      "b1_72h@ros_n",
+      "b1_72h@ros_one",
+      "b1_72h@rovn",
+      "b1_72h@share_cnt",
+      "b1_72h@str",
+      "b1_72h@str_plus",
+      "b2_1h@is_return_1",
+      "b2_1h@is_share",
+      "b2_1h@return_n_uv",
+      "b2_1h@ros",
+      "b2_1h@ros_minus",
+      "b2_1h@ros_n",
+      "b2_1h@ros_one",
+      "b2_1h@rovn",
+      "b2_1h@share_cnt",
+      "b2_1h@str",
+      "b2_1h@str_plus",
+      "b2_24h@is_return_1",
+      "b2_24h@is_share",
+      "b2_24h@return_n_uv",
+      "b2_24h@ros",
+      "b2_24h@ros_minus",
+      "b2_24h@ros_n",
+      "b2_24h@ros_one",
+      "b2_24h@rovn",
+      "b2_24h@share_cnt",
+      "b2_24h@str",
+      "b2_24h@str_plus",
+      "b2_3h@is_return_1",
+      "b2_3h@is_share",
+      "b2_3h@return_n_uv",
+      "b2_3h@ros",
+      "b2_3h@ros_minus",
+      "b2_3h@ros_n",
+      "b2_3h@ros_one",
+      "b2_3h@rovn",
+      "b2_3h@share_cnt",
+      "b2_3h@str",
+      "b2_3h@str_plus",
+      "b3_168h@is_return_1",
+      "b3_168h@is_share",
+      "b3_168h@return_n_uv",
+      "b3_168h@ros",
+      "b3_168h@ros_minus",
+      "b3_168h@ros_n",
+      "b3_168h@ros_one",
+      "b3_168h@rovn",
+      "b3_168h@share_cnt",
+      "b3_168h@str",
+      "b3_168h@str_plus",
+      "b3_24h@is_return_1",
+      "b3_24h@is_share",
+      "b3_24h@return_n_uv",
+      "b3_24h@ros",
+      "b3_24h@ros_minus",
+      "b3_24h@ros_n",
+      "b3_24h@ros_one",
+      "b3_24h@rovn",
+      "b3_24h@share_cnt",
+      "b3_24h@str",
+      "b3_24h@str_plus",
+      "b4_12h@is_return_1",
+      "b4_12h@is_share",
+      "b4_12h@return_n_uv",
+      "b4_12h@ros",
+      "b4_12h@ros_minus",
+      "b4_12h@ros_n",
+      "b4_12h@ros_one",
+      "b4_12h@rovn",
+      "b4_12h@share_cnt",
+      "b4_12h@str",
+      "b4_12h@str_plus",
+      "b4_1h@is_return_1",
+      "b4_1h@is_share",
+      "b4_1h@return_n_uv",
+      "b4_1h@ros",
+      "b4_1h@ros_minus",
+      "b4_1h@ros_n",
+      "b4_1h@ros_one",
+      "b4_1h@rovn",
+      "b4_1h@share_cnt",
+      "b4_1h@str",
+      "b4_1h@str_plus",
+      "b5_168h@is_share",
+      "b5_168h@return_n_uv",
+      "b5_168h@ros",
+      "b5_168h@ros_minus",
+      "b5_168h@ros_n",
+      "b5_168h@ros_one",
+      "b5_168h@rovn",
+      "b5_168h@str",
+      "b5_168h@str_plus",
+      "b5_72h@is_share",
+      "b5_72h@return_n_uv",
+      "b5_72h@ros",
+      "b5_72h@ros_minus",
+      "b5_72h@ros_n",
+      "b5_72h@ros_one",
+      "b5_72h@rovn",
+      "b5_72h@str",
+      "b5_72h@str_plus",
+      "b6_1h@is_share",
+      "b6_1h@return_n_uv",
+      "b6_1h@ros",
+      "b6_1h@ros_minus",
+      "b6_1h@ros_n",
+      "b6_1h@ros_one",
+      "b6_1h@rovn",
+      "b6_1h@str",
+      "b6_1h@str_plus",
+      "b6_24h@is_share",
+      "b6_24h@return_n_uv",
+      "b6_24h@ros",
+      "b6_24h@ros_minus",
+      "b6_24h@ros_n",
+      "b6_24h@ros_one",
+      "b6_24h@rovn",
+      "b6_24h@str",
+      "b6_24h@str_plus",
+      "b7_168h@is_share",
+      "b7_168h@return_n_uv",
+      "b7_168h@ros",
+      "b7_168h@ros_minus",
+      "b7_168h@rovn",
+      "b7_168h@str",
+      "b7_168h@str_plus",
+      "b7_24h@is_share",
+      "b7_24h@return_n_uv",
+      "b7_24h@ros",
+      "b7_24h@ros_minus",
+      "b7_24h@rovn",
+      "b7_24h@str",
+      "b7_24h@str_plus",
+      "b8_24h@is_share",
+      "b8_24h@return_n_uv",
+      "b8_24h@ros",
+      "b8_24h@ros_minus",
+      "b8_24h@rovn",
+      "b8_24h@str",
+      "b8_24h@str_plus",
+      "b9_24h@is_share",
+      "b9_24h@return_n_uv",
+      "b9_24h@ros",
+      "b9_24h@ros_minus",
+      "b9_24h@rovn",
+      "b9_24h@str",
+      "b9_24h@str_plus",
+      "c1_168h@is_return_1",
+      "c1_168h@is_share",
+      "c1_168h@return_n_uv",
+      "c1_168h@ros",
+      "c1_168h@ros_minus",
+      "c1_168h@ros_n",
+      "c1_168h@ros_one",
+      "c1_168h@rovn",
+      "c1_168h@share_cnt",
+      "c1_168h@str",
+      "c1_168h@str_plus",
+      "c1_72h@is_return_1",
+      "c1_72h@is_share",
+      "c1_72h@return_n_uv",
+      "c1_72h@ros",
+      "c1_72h@ros_minus",
+      "c1_72h@ros_n",
+      "c1_72h@ros_one",
+      "c1_72h@rovn",
+      "c1_72h@share_cnt",
+      "c1_72h@str",
+      "c1_72h@str_plus",
+      "c5_tags_1d@avgscore",
+      "c5_tags_1d@matchnum",
+      "c5_tags_1d@maxscore",
+      "c5_tags_3d@avgscore",
+      "c5_tags_3d@matchnum",
+      "c5_tags_3d@maxscore",
+      "c5_tags_7d@avgscore",
+      "c5_tags_7d@matchnum",
+      "c5_tags_7d@maxscore",
+      "c6_tags_1d@avgscore",
+      "c6_tags_1d@matchnum",
+      "c6_tags_1d@maxscore",
+      "c6_tags_3d@avgscore",
+      "c6_tags_3d@matchnum",
+      "c6_tags_3d@maxscore",
+      "c6_tags_7d@avgscore",
+      "c6_tags_7d@matchnum",
+      "c6_tags_7d@maxscore",
+      "c7_return@num",
+      "c7_return@rank",
+      "c7_return@score",
+      "c7_share@num",
+      "c7_share@rank",
+      "c7_share@score",
+      "c8_return@num",
+      "c8_return@rank",
+      "c8_return@score",
+      "c8_share@num",
+      "c8_share@rank",
+      "c8_share@score",
+      "c9@m_r_uv",
+      "c9@m_s_cnt",
+      "c9@r_pv",
+      "c9@r_uv",
+      "c9@ros",
+      "c9@ros_minus",
+      "c9@ros_one",
+      "c9@s_cnt",
+      "c9@s_pv",
+      "c9_c1s@mu",
+      "c9_c1s@ros",
+      "c9_c1s@ros_minus",
+      "c9_c1s@ros_one",
+      "c9_c1s@rp",
+      "c9_c1s@ru",
+      "c9_c1s@sp",
+      "c9_c2s@mu",
+      "c9_c2s@ros",
+      "c9_c2s@ros_minus",
+      "c9_c2s@ros_one",
+      "c9_c2s@rp",
+      "c9_c2s@ru",
+      "c9_c2s@sp",
+      "c9_l1s@mu",
+      "c9_l1s@ros",
+      "c9_l1s@ros_minus",
+      "c9_l1s@ros_one",
+      "c9_l1s@rp",
+      "c9_l1s@ru",
+      "c9_l1s@sp",
+      "c9_l2s@mu",
+      "c9_l2s@ros",
+      "c9_l2s@ros_minus",
+      "c9_l2s@ros_one",
+      "c9_l2s@rp",
+      "c9_l2s@ru",
+      "c9_l2s@sp",
+      "c9_lrs@1@title",
+      "c9_lrs@1@ts",
+      "c9_lrs@1@uv",
+      "c9_lrs@2@title",
+      "c9_lrs@2@ts",
+      "c9_lrs@2@uv",
+      "c9_lss@1@cnt",
+      "c9_lss@1@title",
+      "c9_lss@1@ts",
+      "c9_lss@2@cnt",
+      "c9_lss@2@title",
+      "c9_lss@2@ts",
+      "c9_mrs@1@title",
+      "c9_mrs@1@ts",
+      "c9_mrs@1@uv",
+      "c9_mrs@2@title",
+      "c9_mrs@2@ts",
+      "c9_mrs@2@uv",
+      "c9_mss@1@cnt",
+      "c9_mss@1@title",
+      "c9_mss@1@ts",
+      "c9_mss@2@cnt",
+      "c9_mss@2@title",
+      "c9_mss@2@ts",
+      "d1@ros_cf_rank",
+      "d1@ros_cf_score",
+      "d1@rov_cf_rank",
+      "d1@rov_cf_score",
+      "d2@rank",
+      "d2@score",
+      "d3@exp",
+      "d3@return_n",
+      "d3@rovn",
+      "h@bit_rate",
+      "h@total_time",
+      "h@ts",
+      "h@tt@1",
+      "hour",
+      "hr_sim@cate2",
+      "hr_sim@cate2_list",
+      "hr_sim@keywords",
+      "hr_sim@title",
+      "r@bit_rate",
+      "r@total_time",
+      "r@ts",
+      "r@tt@1"
+      ]
+    }
+  }
+}

recommend-server-service/src/main/resources/feeds_score_config_xgb_ros_binary_20250319.conf

@@ -0,0 +1,244 @@
+scorer-config = {
+  rov-score-config = {
+    scorer-name = "com.tzld.piaoquan.recommend.server.service.score.XGBoostScorer"
+    scorer-priority = 99
+    model-path = "zhangbo/model_xgb_for_ros_binary_v1.tar.gz"
+    param = {
+      localDir = "xgboost/model_xgb_for_ros_binary_v1"
+      features = [
+            "b1_return_1_uv_24h"
+            "b1_return_1_uv_3h"
+            "b1_ros_24h"
+            "b1_ros_3h"
+            "b1_ros_minus_24h"
+            "b1_ros_minus_3h"
+            "b1_ros_one_24h"
+            "b1_ros_one_3h"
+            "b1_rovn_24h"
+            "b1_rovn_3h"
+            "b1_str_one_24h"
+            "b1_str_one_3h"
+            "b2_return_n_uv_24h"
+            "b2_return_n_uv_3h"
+            "b2_ros_24h"
+            "b2_ros_3h"
+            "b2_ros_minus_24h"
+            "b2_ros_minus_3h"
+            "b2_ros_one_24h"
+            "b2_ros_one_3h"
+            "b2_rovn_24h"
+            "b2_rovn_3h"
+            "b2_str_one_24h"
+            "b2_str_one_3h"
+            "b3_return_n_uv_168h"
+            "b3_return_n_uv_24h"
+            "b3_ros_168h"
+            "b3_ros_24h"
+            "b3_ros_minus_168h"
+            "b3_ros_minus_24h"
+            "b3_ros_one_168h"
+            "b3_ros_one_24h"
+            "b3_rovn_168h"
+            "b3_rovn_24h"
+            "b3_str_one_168h"
+            "b3_str_one_24h"
+            "b5_return_n_uv_24h"
+            "b5_ros_24h"
+            "b5_ros_minus_24h"
+            "b5_ros_one_24h"
+            "b5_rovn_24h"
+            "b5_str_one_24h"
+            "b6_return_n_uv_24h"
+            "b6_ros_24h"
+            "b6_ros_minus_24h"
+            "b6_ros_one_24h"
+            "b6_rovn_24h"
+            "b6_str_one_24h"
+            "b7_return_n_uv_24h"
+            "b7_ros_24h"
+            "b7_ros_minus_24h"
+            "b7_ros_one_24h"
+            "b7_rovn_24h"
+            "b7_str_one_24h"
+            "b8_return_n_uv_24h"
+            "b8_ros_24h"
+            "b8_ros_minus_24h"
+            "b8_ros_one_24h"
+            "b8_rovn_24h"
+            "b8_str_one_24h"
+            "b9_return_n_uv_24h"
+            "b9_ros_24h"
+            "b9_ros_minus_24h"
+            "b9_ros_one_24h"
+            "b9_rovn_24h"
+            "b9_str_one_24h"
+            "b11_return_n_uv_24h"
+            "b11_ros_24h"
+            "b11_ros_minus_24h"
+            "b11_ros_one_24h"
+            "b11_rovn_24h"
+            "b11_str_one_24h"
+            "b12_return_n_uv_14d"
+            "b12_ros_14d"
+            "b12_ros_minus_14d"
+            "b12_ros_one_14d"
+            "b12_rovn_14d"
+            "b12_str_one_14d"
+            "b13_return_n_uv_24h"
+            "b13_return_n_uv_3h"
+            "b13_ros_24h"
+            "b13_ros_3h"
+            "b13_ros_minus_24h"
+            "b13_ros_minus_3h"
+            "b13_ros_one_24h"
+            "b13_ros_one_3h"
+            "b13_rovn_24h"
+            "b13_rovn_3h"
+            "b13_str_one_24h"
+            "b13_str_one_3h"
+            "c1_click_12h"
+            "c1_click_168h"
+            "c1_click_24h"
+            "c1_click_72h"
+            "c1_return_1_uv_12h"
+            "c1_return_1_uv_168h"
+            "c1_return_1_uv_24h"
+            "c1_return_1_uv_72h"
+            "c1_ros_12h"
+            "c1_ros_168h"
+            "c1_ros_24h"
+            "c1_ros_72h"
+            "c1_ros_minus_12h"
+            "c1_ros_minus_168h"
+            "c1_ros_minus_24h"
+            "c1_ros_minus_72h"
+            "c1_ros_one_12h"
+            "c1_ros_one_168h"
+            "c1_ros_one_24h"
+            "c1_ros_one_72h"
+            "c1_rovn_12h"
+            "c1_rovn_168h"
+            "c1_rovn_24h"
+            "c1_rovn_72h"
+            "c1_str_one_12h"
+            "c1_str_one_168h"
+            "c1_str_one_24h"
+            "c1_str_one_72h"
+            "c2_click_12h"
+            "c2_click_168h"
+            "c2_click_24h"
+            "c2_click_72h"
+            "c2_is_return_1_12h"
+            "c2_is_return_1_168h"
+            "c2_is_return_1_24h"
+            "c2_is_return_1_72h"
+            "c2_is_share_12h"
+            "c2_is_share_168h"
+            "c2_is_share_24h"
+            "c2_is_share_72h"
+            "c2_return_n_uv_12h"
+            "c2_return_n_uv_168h"
+            "c2_return_n_uv_24h"
+            "c2_return_n_uv_72h"
+            "c2_share_cnt_12h"
+            "c2_share_cnt_168h"
+            "c2_share_cnt_24h"
+            "c2_share_cnt_72h"
+            "c3_click_12h"
+            "c3_click_168h"
+            "c3_click_24h"
+            "c3_click_72h"
+            "c3_is_return_1_12h"
+            "c3_is_return_1_168h"
+            "c3_is_return_1_24h"
+            "c3_is_return_1_72h"
+            "c3_is_share_12h"
+            "c3_is_share_168h"
+            "c3_is_share_24h"
+            "c3_is_share_72h"
+            "c3_return_n_uv_12h"
+            "c3_return_n_uv_168h"
+            "c3_return_n_uv_24h"
+            "c3_return_n_uv_72h"
+            "c3_share_cnt_12h"
+            "c3_share_cnt_168h"
+            "c3_share_cnt_24h"
+            "c3_share_cnt_72h"
+            "c4_avg_ros_168h"
+            "c4_avg_ros_24h"
+            "c4_avg_ros_72h"
+            "c4_avg_ros_minus_168h"
+            "c4_avg_ros_minus_24h"
+            "c4_avg_ros_minus_72h"
+            "c4_avg_ros_one_168h"
+            "c4_avg_ros_one_24h"
+            "c4_avg_ros_one_72h"
+            "c4_avg_rovn_168h"
+            "c4_avg_rovn_24h"
+            "c4_avg_rovn_72h"
+            "c4_avg_str_one_168h"
+            "c4_avg_str_one_24h"
+            "c4_avg_str_one_72h"
+            "c4_diff_ros_168h"
+            "c4_diff_ros_24h"
+            "c4_diff_ros_72h"
+            "c4_diff_ros_minus_168h"
+            "c4_diff_ros_minus_24h"
+            "c4_diff_ros_minus_72h"
+            "c4_diff_ros_one_168h"
+            "c4_diff_ros_one_24h"
+            "c4_diff_ros_one_72h"
+            "c4_diff_rovn_168h"
+            "c4_diff_rovn_24h"
+            "c4_diff_rovn_72h"
+            "c4_diff_str_one_168h"
+            "c4_diff_str_one_24h"
+            "c4_diff_str_one_72h"
+            "c5_avgscore_tags_1d"
+            "c5_avgscore_tags_3d"
+            "c5_avgscore_tags_7d"
+            "c5_matchnum_tags_1d"
+            "c5_matchnum_tags_3d"
+            "c5_matchnum_tags_7d"
+            "c5_maxscore_tags_1d"
+            "c5_maxscore_tags_3d"
+            "c5_maxscore_tags_7d"
+            "c6_avgscore_tags_1d"
+            "c6_avgscore_tags_3d"
+            "c6_avgscore_tags_7d"
+            "c6_matchnum_tags_1d"
+            "c6_matchnum_tags_3d"
+            "c6_matchnum_tags_7d"
+            "c6_maxscore_tags_1d"
+            "c6_maxscore_tags_3d"
+            "c6_maxscore_tags_7d"
+            "d1_ros_cf_rank"
+            "d1_ros_cf_score"
+            "d1_rov_cf_rank"
+            "d1_rov_cf_score"
+            "d2_rank"
+            "d2_score"
+            "d3_exp"
+            "d3_return_n"
+            "d3_rovn"
+            "festive_sim"
+            "head_title_festive_sim"
+            "head_title_merge1_sim"
+            "head_title_merge2_sim"
+            "merge1_sim"
+            "merge2_sim"
+            "title_sim"
+            "day_of_week"
+            "hour"
+            "create_ts_diff"
+            "is_greeting"
+            "total_time"
+            "width"
+            "height"
+            "width/height"
+            "size"
+            "bit_rate"
+      ]
+    }
+  }
+}