feat:添加V570召回策略实验,基于V569移除8路召回

V570 在 V569 基础上移除以下 8 路召回策略,验证候选池剪枝对推荐指标的影响:
- 5 路 OldSpecial: recall_pool_region_h / recall_pool_24h / recall_pool_region_24h / rov_recall_24h_dup / rov_recall_h_h
- 3 路 priori: priori_province_rovn / priori_province_str / priori_province_ros

hotspot (recall_strategy_hotspot) 属于流量池通道,本次不动。

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

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

@@ -37,6 +37,7 @@ public class RankRouter {
         STRATEGY_CLASSES.put("566", RankStrategy4RegionMergeModelV566.class);
         STRATEGY_CLASSES.put("567", RankStrategy4RegionMergeModelV567.class);
         STRATEGY_CLASSES.put("569", RankStrategy4RegionMergeModelV569.class);
+        STRATEGY_CLASSES.put("570", RankStrategy4RegionMergeModelV570.class);
         STRATEGY_CLASSES.put("568", RankStrategy4RegionMergeModelV568.class);
         STRATEGY_CLASSES.put("839", RankStrategy4RegionMergeModelV839.class);
         STRATEGY_CLASSES.put(relevantRank, RankStrategy4RelevantModelV1.class);

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RegionMergeModelV570.java

@@ -0,0 +1,446 @@
+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.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.UserShareReturnProfile;
+import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractVideoMergeCate;
+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.*;
+import lombok.extern.slf4j.Slf4j;
+import org.apache.commons.collections4.MapUtils;
+import org.apache.commons.lang3.StringUtils;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.stereotype.Service;
+
+import java.util.*;
+import java.util.concurrent.Future;
+import java.util.concurrent.TimeUnit;
+
+/**
+ * V570 实验：基于 V569,移除以下 8 路召回
+ *   - recall_pool_region_h     (RegionHRecallStrategy)
+ *   - recall_pool_24h          (RegionRelative24HRecallStrategy)
+ *   - recall_pool_region_24h   (Region24HRecallStrategy)
+ *   - rov_recall_24h_dup       (RegionRelative24HDupRecallStrategy)
+ *   - rov_recall_h_h           (RegionHDupRecallStrategy)
+ *   - priori_province_rovn     (PrioriProvinceRovnRecallStrategy)
+ *   - priori_province_str      (PrioriProvinceStrRecallStrategy)
+ *   - priori_province_ros      (PrioriProvinceRosRecallStrategy)
+ */
+@Service
+@Slf4j
+public class RankStrategy4RegionMergeModelV570 extends RankStrategy4RegionMergeModelBasic {
+    @ApolloJsonValue("${rank.score.merge.weightv570:}")
+    private Map<String, Double> mergeWeight;
+
+    @Autowired
+    private FeatureService featureService;
+
+    @Override
+    public List<Video> mergeAndRankRovRecall(RankParam param) {
+        Map<String, Double> mergeWeight = this.mergeWeight != null ? this.mergeWeight : new HashMap<>(0);
+
+        //-------------------融-------------------
+        //-------------------合-------------------
+        //-------------------逻-------------------
+        //-------------------辑-------------------
+
+        long currentMs = System.currentTimeMillis();
+        Set<Long> setVideo = new HashSet<>();
+        setVideo.add(param.getHeadVid());
+        List<Video> rovRecallRank = new ArrayList<>();
+        // V570: 移除 5 路特殊旧召回 (RegionH / RegionHDup / Region24H / RegionRelative24H / RegionRelative24HDup)
+        //-------------------return相似召回------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("v6", 5.0).intValue(), param, ReturnVideoRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        //-------------------新地域召回------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("v1", 5.0).intValue(), param, RegionRealtimeRecallStrategyV1.PUSH_FORM, setVideo, rovRecallRank);
+        //-------------------scene cf rovn------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("sceneCFRovn", 5.0).intValue(), param, SceneCFRovnRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        //-------------------scene cf rosn------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("sceneCFRosn", 5.0).intValue(), param, SceneCFRosnRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        // -------------------user cate1------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("cate1RecallN", 5.0).intValue(), param, UserCate1RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        // -------------------user cate2------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("cate2RecallN", 5.0).intValue(), param, UserCate2RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        // -------------------head province cate1------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("headCate1RecallN", 3.0).intValue(), param, HeadProvinceCate1RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        // -------------------head province cate2------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("headCate2RecallN", 3.0).intValue(), param, HeadProvinceCate2RecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        //-------------------head cate2 of rovn------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("headCate2Rov", 5.0).intValue(), param, HeadCate2RovRecallStrategy.PUSH_FROM, setVideo, rovRecallRank);
+        //-------------------city rovn------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("cityRov", 5.0).intValue(), param, CityRovnRecallStrategy.PUSH_FROM, setVideo, rovRecallRank);
+        // V570: 移除 priori_province_rovn / priori_province_str / priori_province_ros
+        //-------------------return1 cate2 ros------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("return1Cate2Ros", 5.0).intValue(), param, Return1Cate2RosRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        //-------------------return1 cate2 str------------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("return1Cate2Str", 5.0).intValue(), param, Return1Cate2StrRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+        //--------------deconstruction keywords ros-------------
+        RecallUtils.extractRecall(mergeWeight.getOrDefault("deconstructionKeywordsRos", 5.0).intValue(), param, UserDeconstructionKeywordsRecallStrategy.PUSH_FORM, setVideo, rovRecallRank);
+
+        // 记录召回源中的视频
+        this.rankBeforePostProcessor(rovRecallRank);
+
+        //-------------------排-------------------
+        //-------------------序-------------------
+        //-------------------逻-------------------
+        //-------------------辑-------------------
+        Map<String, String> rtFeatureDumpsMap = dumpsRtFeature(param.getUserRTShareList());
+
+        // 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
+        Map<String, String> headVideoInfo = param.getHeadInfo();
+        List<String> vids = CommonCollectionUtils.toListDistinct(rovRecallRank, v -> String.valueOf(v.getVideoId()));
+        Map<String, Map<String, Map<String, String>>> videoBaseInfoMap = featureService.getVideoBaseInfo("", vids);
+        Map<String, Map<String, Map<String, String>>> videoBCData = featureService.getVideoStatistics(vids);
+
+        FeatureService.Feature feature = featureService.getFeatureV4(param, headVideoInfo, videoBaseInfoMap, vids);
+        Map<String, Map<String, String>> featureOriginUser = feature.getUserFeature();
+        Map<String, Map<String, Map<String, String>>> featureOriginVideo = feature.getVideoFeature();
+
+        // 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 = param.getBehaviorVideos();
+        Map<String, String> creativeInfo = param.getCreativeInfoFeature();
+
+        // 3. 特征处理
+        List<RankItem> rankItems = CommonCollectionUtils.toList(rovRecallRank, RankItem::new);
+        Map<String, Float> userFeatureMap = getUserFeature(currentMs, param, creativeInfo, headVideoInfo, userProfile, featureOriginUser);
+        batchGetVideoFeature(currentMs, userProfile, creativeInfo, headVideoInfo, videoBaseInfoMap,
+                newC7Map, newC8Map, featureOriginUser, userBehaviorVideoMap, featureOriginVideo, rankItems);
+
+        // 4. 排序模型计算
+        Map<String, Float> sceneFeatureMap = new HashMap<>(0);
+        List<RankItem> items = ScorerUtils.getScorerPipeline("feeds_score_config_str_and_ros_20260319.conf").scoring(sceneFeatureMap, userFeatureMap, userFeatureMap, rankItems);
+
+        // 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", 1.15);
+
+        double rosAdd = mergeWeight.getOrDefault("ros_add", 0.1);
+        double rosW = mergeWeight.getOrDefault("ros_w", 1.0d);
+
+        double vorAdd = mergeWeight.getOrDefault("vor_add", 0.1d);
+        double vorW = mergeWeight.getOrDefault("vor_w", 1.0d);
+
+        double c1Rovn1hW = mergeWeight.getOrDefault("c1_rovn_1h_w", 0d);
+        double c1Rovn24hW = mergeWeight.getOrDefault("c1_rovn_24h_w", 0d);
+
+        double b0Str1hW = mergeWeight.getOrDefault("b0_str_1h_w", 0d);
+        double b0Str24hW = mergeWeight.getOrDefault("b0_str_24h_w", 0d);
+
+        double b0Ror1hW = mergeWeight.getOrDefault("b0_ror_1h_w", 0d);
+        double b0Ror24hW = mergeWeight.getOrDefault("b0_ror_24h_w", 0d);
+
+        Map<String, Map<String, String>> vid2MapFeature = this.getVideoRedisFeature(vids, "redis:vid_hasreturn_vor:");
+
+        // 获取权重
+        Map<String, String> contextInfo = getContextInfo(param);
+
+        List<Video> result = new ArrayList<>();
+        for (RankItem item : items) {
+            double score;
+            double fmRovOrigin = item.getScoreRov();
+            item.getScoresMap().put("fmRovOrigin", 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);
+
+            double norXGBScore = item.getScoresMap().getOrDefault("NorXGBScore", 0d);
+            double newNorXGBScore = norPowerCalibration(xgbNorPowerWeight, xgbNorPowerExp, norXGBScore);
+            item.getScoresMap().put("rosAdd", rosAdd);
+            item.getScoresMap().put("rosW", rosW);
+
+            double vor = Double.parseDouble(vid2MapFeature.getOrDefault(item.getVideoId() + "", new HashMap<>()).getOrDefault("vor", "0"));
+            item.getScoresMap().put("vor", vor);
+            item.getScoresMap().put("vorAdd", vorAdd);
+            item.getScoresMap().put("vorW", vorW);
+
+            Map<String, String> bcData = videoBCData.getOrDefault(String.valueOf(item.getVideoId()), new HashMap<>()).getOrDefault("alg_vid_feature_b_c_data", new HashMap<>());
+
+            double c1Rovn1h = Double.parseDouble(bcData.getOrDefault("c1_rovn_1h", "0"));
+            double c1Rovn24h = Double.parseDouble(bcData.getOrDefault("c1_rovn_24h", "0"));
+            double c1RovnScore = c1Rovn1hW * c1Rovn1h + c1Rovn24hW * c1Rovn24h;
+            item.getScoresMap().put("c1RovnScore", c1RovnScore);
+            item.getScoresMap().put("c1Rovn1hW", c1Rovn1hW);
+            item.getScoresMap().put("c1Rovn1h", c1Rovn1h);
+            item.getScoresMap().put("c1Rovn24hW", c1Rovn24hW);
+            item.getScoresMap().put("c1Rovn24h", c1Rovn24h);
+
+            double b0Str1h = Double.parseDouble(bcData.getOrDefault("b_str1_1h", "0"));
+            double b0Str24h = Double.parseDouble(bcData.getOrDefault("b_str1_24h", "0"));
+            double b0StrScore = b0Str1hW * b0Str1h + b0Str24hW * b0Str24h;
+            item.getScoresMap().put("b0StrScore", b0StrScore);
+            item.getScoresMap().put("b0Str1hW", b0Str1hW);
+            item.getScoresMap().put("b0Str1h", b0Str1h);
+            item.getScoresMap().put("b0Str24hW", b0Str24hW);
+            item.getScoresMap().put("b0Str24h", b0Str24h);
+
+            double b0Ror1h = Double.parseDouble(bcData.getOrDefault("b_ror1_1h", "0"));
+            double b0Ror24h = Double.parseDouble(bcData.getOrDefault("b_ror1_24h", "0"));
+            double b0RorScore = b0Ror1hW * b0Ror1h + b0Ror24hW * b0Ror24h;
+            item.getScoresMap().put("b0RorScore", b0RorScore);
+            item.getScoresMap().put("b0Ror1hW", b0Ror1hW);
+            item.getScoresMap().put("b0Ror1h", b0Ror1h);
+            item.getScoresMap().put("b0Ror24hW", b0Ror24hW);
+            item.getScoresMap().put("b0Ror24h", b0Ror24h);
+
+            score = fmRov * (rosAdd + rosW * newNorXGBScore) * (vorAdd + vorW * vor) + c1RovnScore + b0StrScore + b0RorScore;
+
+            Video video = item.getVideo();
+            video.setScore(score);
+            video.setSortScore(score);
+            video.setScoresMap(item.getScoresMap());
+            video.setAllFeatureMap(item.getAllFeatureMap());
+
+            String mergeCate2 = ExtractVideoMergeCate.parseMergeCate2(String.valueOf(item.getVideoId()), videoBaseInfoMap);
+            if (StringUtils.isNotBlank(mergeCate2)) {
+                video.getMergeCateList().add(mergeCate2);
+            }
+
+            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());
+            }
+            if (null != rtFeatureDumpsMap && !rtFeatureDumpsMap.isEmpty()) {
+                video.getMetaFeatureMap().put("rt", rtFeatureDumpsMap);
+            }
+            if (MapUtils.isNotEmpty(param.getCreativeInfoFeature())) {
+                video.getMetaFeatureMap().put("creativeInfo", param.getCreativeInfoFeature());
+            }
+            if (MapUtils.isNotEmpty(contextInfo)) {
+                video.getMetaFeatureMap().put("context", contextInfo);
+            }
+            if (Objects.nonNull(video.getRankVideoInfoMap()) && video.getRankVideoInfoMap().containsKey(video.getVideoId())){
+                video.getRankVideoInfoMap().get(video.getVideoId()).setScore(score);
+                video.getRankVideoInfoMap().get(video.getVideoId()).setScoresMap(video.getScoresMap());
+            }
+            result.add(video);
+        }
+        ExtractVideoMergeCate.addOtherParam(result, videoBaseInfoMap);
+        result.sort(Comparator.comparingDouble(o -> -o.getSortScore()));
+        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, Float> getUserFeature(long currentMs, RankParam param, Map<String, String> creativeInfo, Map<String, String> headInfo, UserShareReturnProfile userProfile, Map<String, Map<String, String>> userOriginInfo) {
+        Map<String, Double> featMap = new HashMap<>();
+        // context feature
+        String appType = String.valueOf(param.getAppType());
+        String hotSceneType = String.valueOf(param.getHotSceneType());
+        FeatureV6.getContextFeature(currentMs, appType, hotSceneType, featMap);
+        FeatureV6.getCreativeBaseFeature("e1", creativeInfo, featMap);
+
+        // head video feature
+        FeatureV6.getVideoBaseFeature("h", currentMs, headInfo, featMap);
+
+        // user feature
+        Map<String, String> baseInfo = getUserBaseInfo(param);
+        FeatureV6.getUserFeature(userOriginInfo, featMap);
+        FeatureV6.getUserProfileFeature(userProfile, baseInfo, featMap);
+
+        return FeatureBucketUtils.noBucketFeature(featMap);
+    }
+
+    private Map<String, Float> getVideoFeature(long currentMs, String vid,
+                                               UserShareReturnProfile userProfile,
+                                               Map<String, String> creativeInfo,
+                                               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
+        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
+        FeatureV6.getVideoBaseFeature("r", currentMs, rankInfo, featMap);
+        FeatureV6.getVideoFeature(vid, videoOriginInfo, featMap);
+
+        // head&rank cross feature
+        FeatureV6.getHeadRankVideoCrossFeature(headInfo, rankInfo, featMap);
+        FeatureV6.getCreativeCrossFeature("e1", creativeInfo, rankInfo, featMap);
+
+        // user profile & rank cross
+        FeatureV6.getProfileVideoCrossFeature(currentMs, userProfile, rankInfo, historyVideoMap, featMap);
+
+        return FeatureBucketUtils.noBucketFeature(featMap);
+    }
+
+    private void batchGetVideoFeature(long currentMs,
+                                      UserShareReturnProfile userProfile,
+                                      Map<String, String> creativeInfo,
+                                      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.featureMap = getVideoFeature(currentMs, vid, userProfile, creativeInfo, headInfo, rankInfo, c7Map, c8Map, userOriginInfo, historyVideoMap, videoOriginInfo);
+                    item.norFeatureMap = item.featureMap;
+                    return 1;
+                });
+                futures.add(future);
+            }
+
+            try {
+                for (Future<Integer> future : futures) {
+                    future.get(1000, TimeUnit.MILLISECONDS);
+                }
+            } catch (Exception e) {
+                log.error("get feature error", e);
+            }
+            // 超时后取消
+            for (Future<Integer> future : futures) {
+                try {
+                    if (!future.isDone()) {
+                        future.cancel(true);
+                    }
+                } catch (Exception e) {
+                    log.error("cancel 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);
+            }
+        }
+        String userChannel = param.getChannelName();
+        if (null != userChannel && !userChannel.isEmpty()) {
+            baseInfo.put("user_channel", userChannel);
+        }
+        if (FeatureUtils.firstLevel(param.getUserShareDepth())) {
+            baseInfo.put("user_level", "1st");
+        }
+        return baseInfo;
+    }
+
+    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 Map<String, Double> findSimCateScore(String headCate2, int length) {
+        if (StringUtils.isBlank(headCate2)) {
+            return new HashMap<>();
+        }
+
+        String redisKey = String.format("alg_recsys_good_cate_pair_list:%s", headCate2);
+        String cate2Value = redisTemplate.opsForValue().get(redisKey);
+        if (StringUtils.isEmpty(cate2Value)) {
+            return new HashMap<>();
+        }
+
+        return this.parsePair(cate2Value, length);
+    }
+
+    private Map<String, Double> parsePair(String value, int length) {
+        if (StringUtils.isBlank(value)) {
+            return new HashMap<>();
+        }
+
+        String[] split = value.split("\t");
+        if (split.length != 2) {
+            return new HashMap<>();
+        }
+
+        String[] valueList = split[0].trim().split(",");
+        String[] scoreList = split[1].trim().split(",");
+        if (valueList.length != scoreList.length) {
+            return new HashMap<>();
+        }
+
+        int minLength = Math.min(length, valueList.length);
+        Map<String, Double> resultMap = new HashMap<>();
+        for (int i = 0; i < minLength; i++) {
+            resultMap.put(valueList[i].trim(), Double.parseDouble(scoreList[i].trim()));
+        }
+
+        return resultMap;
+    }
+
+    private String findVideoMergeCate2(Map<String, Map<String, Map<String, String>>> featureOriginVideo, String vid) {
+        Map<String, String> videoInfo = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
+        return videoInfo.get("merge_second_level_cate");
+    }
+}