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@@ -1,14 +1,25 @@
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package com.tzld.piaoquan.recommend.server.service.rank.strategy;
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import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
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+import com.tzld.piaoquan.recommend.server.common.ThreadPoolFactory;
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+import com.tzld.piaoquan.recommend.server.common.base.RankItem;
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import com.tzld.piaoquan.recommend.server.model.Video;
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+import com.tzld.piaoquan.recommend.server.service.FeatureService;
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import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
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+import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
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+import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
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+import com.tzld.piaoquan.recommend.server.service.score.ScorerUtils;
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+import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
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import lombok.extern.slf4j.Slf4j;
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+import org.apache.commons.collections4.MapUtils;
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import org.apache.commons.math3.util.Pair;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Service;
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import java.util.*;
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+import java.util.concurrent.Future;
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+import java.util.concurrent.TimeUnit;
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+import java.util.stream.Collectors;
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@Service
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@Slf4j
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@@ -17,52 +28,379 @@ public class RankStrategy4RegionMergeModelV562 extends RankStrategy4RegionMergeM
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private Map<String, Double> mergeWeight;
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@Autowired
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- private RankStrategy4RegionMergeModelV563 modelV563Service;
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+ private FeatureService featureService;
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@Override
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public List<Video> mergeAndRankRovRecall(RankParam param) {
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Map<String, Double> mergeWeight = this.mergeWeight != null ? this.mergeWeight : new HashMap<>(0);
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+ //-------------------融-------------------
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+ //-------------------合-------------------
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+ //-------------------逻-------------------
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+ //-------------------辑-------------------
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- List<Video> result = modelV563Service.mergeAndRankRovRecall(param);
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- if (null != result && !result.isEmpty()) {
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- try {
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- int sortType = mergeWeight.getOrDefault("sortType", 0D).intValue();
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- if (sortType > 0) {
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- String scoreKey;
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- if (1 == sortType) {
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- scoreKey = "fmRov";
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- } else {
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- scoreKey = "hasReturnRovScore";
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+ List<Video> oldRovs = new ArrayList<>();
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+ oldRovs.addAll(extractAndSort(param, RegionHRecallStrategy.PUSH_FORM));
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+ oldRovs.addAll(extractAndSort(param, RegionHDupRecallStrategy.PUSH_FORM));
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+ oldRovs.addAll(extractAndSort(param, Region24HRecallStrategy.PUSH_FORM));
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+ oldRovs.addAll(extractAndSort(param, RegionRelative24HRecallStrategy.PUSH_FORM));
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+ oldRovs.addAll(extractAndSort(param, RegionRelative24HDupRecallStrategy.PUSH_FORM));
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+ removeDuplicate(oldRovs);
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+ int sizeReturn = param.getSize();
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+ List<Video> v0 = oldRovs.size() <= sizeReturn
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+ ? oldRovs
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+ : oldRovs.subList(0, sizeReturn);
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+ Set<Long> setVideo = new HashSet<>();
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+ this.duplicate(setVideo, v0);
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+ setVideo.addAll(v0.stream().map(Video::getVideoId).collect(Collectors.toSet()));
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+ List<Video> rovRecallRank = new ArrayList<>(v0);
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+ //-------------------return相似召回------------------
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+ List<Video> v6 = extractAndSort(param, ReturnVideoRecallStrategy.PUSH_FORM);
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+ v6 = v6.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
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+ v6 = v6.subList(0, Math.min(mergeWeight.getOrDefault("v6", 5.0).intValue(), v6.size()));
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+ rovRecallRank.addAll(v6);
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+ setVideo.addAll(v6.stream().map(Video::getVideoId).collect(Collectors.toSet()));
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+ //-------------------新地域召回------------------
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+ List<Video> v1 = extractAndSort(param, RegionRealtimeRecallStrategyV1.PUSH_FORM);
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+ v1 = v1.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
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+ v1 = v1.subList(0, Math.min(mergeWeight.getOrDefault("v1", 5.0).intValue(), v1.size()));
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+ rovRecallRank.addAll(v1);
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+ setVideo.addAll(v1.stream().map(Video::getVideoId).collect(Collectors.toSet()));
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+ //-------------------scene cf rovn------------------
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+ List<Video> sceneCFRovn = extractAndSort(param, SceneCFRovnRecallStrategy.PUSH_FORM);
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+ sceneCFRovn = sceneCFRovn.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
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+ sceneCFRovn = sceneCFRovn.subList(0, Math.min(mergeWeight.getOrDefault("sceneCFRovn", 5.0).intValue(), sceneCFRovn.size()));
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+ rovRecallRank.addAll(sceneCFRovn);
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+ setVideo.addAll(sceneCFRovn.stream().map(Video::getVideoId).collect(Collectors.toSet()));
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+ //-------------------scene cf rosn------------------
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+ List<Video> sceneCFRosn = extractAndSort(param, SceneCFRosnRecallStrategy.PUSH_FORM);
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+ sceneCFRosn = sceneCFRosn.stream().filter(r -> !setVideo.contains(r.getVideoId())).collect(Collectors.toList());
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+ sceneCFRosn = sceneCFRosn.subList(0, Math.min(mergeWeight.getOrDefault("sceneCFRosn", 5.0).intValue(), sceneCFRosn.size()));
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+ rovRecallRank.addAll(sceneCFRosn);
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+ setVideo.addAll(sceneCFRosn.stream().map(Video::getVideoId).collect(Collectors.toSet()));
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+
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+ //-------------------排-------------------
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+ //-------------------序-------------------
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+ //-------------------逻-------------------
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+ //-------------------辑-------------------
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+
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+ // 1 批量获取特征 省份参数要对齐 headvid 要传递过来!
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+ List<String> vids = CommonCollectionUtils.toListDistinct(rovRecallRank, v -> String.valueOf(v.getVideoId()));
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+
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+ // k1:视频、k2:表、k3:特征、v:特征值
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+ String provinceCn = param.getProvince().replaceAll("省$", "");
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+ String headVid = String.valueOf(param.getHeadVid());
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+ FeatureService.Feature feature = featureService.getFeature(param.getMid(), vids,
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+ String.valueOf(param.getAppType()), provinceCn, headVid);
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+ Map<String, Map<String, String>> featureOriginUser = feature.getUserFeature();
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+ Map<String, Map<String, Map<String, String>>> featureOriginVideo = feature.getVideoFeature();
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+
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+
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+ // 2 特征处理
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+ Map<String, Double> userFeatureMapDouble = new HashMap<>();
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+ String mid = param.getMid();
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+ Map<String, String> c1 = featureOriginUser.getOrDefault("alg_mid_feature_play", new HashMap<>());
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+ Map<String, String> c2 = featureOriginUser.getOrDefault("alg_mid_feature_share_and_return", new HashMap<>());
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+ Map<String, String> c3 = featureOriginUser.getOrDefault("alg_mid_feature_play_tags", new HashMap<>());
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+ Map<String, String> c4 = featureOriginUser.getOrDefault("alg_mid_feature_return_tags", new HashMap<>());
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+ Map<String, String> c5 = featureOriginUser.getOrDefault("alg_mid_feature_share_tags", new HashMap<>());
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+ Map<String, String> c6 = featureOriginUser.getOrDefault("alg_mid_feature_feed_exp_share_tags_v2", new HashMap<>());
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+ Map<String, String> c7 = featureOriginUser.getOrDefault("alg_mid_feature_feed_exp_return_tags_v2", new HashMap<>());
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+ Map<String, String> c8 = featureOriginUser.getOrDefault("alg_mid_feature_sharecf", new HashMap<>());
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+ Map<String, String> c9 = featureOriginUser.getOrDefault("alg_mid_feature_returncf", new HashMap<>());
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+
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+ if (!c1.isEmpty()) {
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+ userFeatureMapDouble.put("playcnt_6h", Double.parseDouble(c1.getOrDefault("playcnt_6h", "0")));
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+ userFeatureMapDouble.put("playcnt_1d", Double.parseDouble(c1.getOrDefault("playcnt_1d", "0")));
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+ userFeatureMapDouble.put("playcnt_3d", Double.parseDouble(c1.getOrDefault("playcnt_3d", "0")));
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+ userFeatureMapDouble.put("playcnt_7d", Double.parseDouble(c1.getOrDefault("playcnt_7d", "0")));
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+ }
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+ if (!c2.isEmpty()) {
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+ userFeatureMapDouble.put("share_pv_12h", Double.parseDouble(c2.getOrDefault("share_pv_12h", "0")));
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+ userFeatureMapDouble.put("share_pv_1d", Double.parseDouble(c2.getOrDefault("share_pv_1d", "0")));
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+ userFeatureMapDouble.put("share_pv_3d", Double.parseDouble(c2.getOrDefault("share_pv_3d", "0")));
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+ userFeatureMapDouble.put("share_pv_7d", Double.parseDouble(c2.getOrDefault("share_pv_7d", "0")));
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+ userFeatureMapDouble.put("return_uv_12h", Double.parseDouble(c2.getOrDefault("return_uv_12h", "0")));
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+ userFeatureMapDouble.put("return_uv_1d", Double.parseDouble(c2.getOrDefault("return_uv_1d", "0")));
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+ userFeatureMapDouble.put("return_uv_3d", Double.parseDouble(c2.getOrDefault("return_uv_3d", "0")));
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+ userFeatureMapDouble.put("return_uv_7d", Double.parseDouble(c2.getOrDefault("return_uv_7d", "0")));
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+ }
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+
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+ Map<String, String> c34567Map = new HashMap<>(15);
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+ List<Tuple2> tmpList0 = Arrays.asList(
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+ new Tuple2(c3, "c3_feature"),
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+ new Tuple2(c4, "c4_feature"),
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+ new Tuple2(c5, "c5_feature"),
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+ new Tuple2(c6, "c6_feature"),
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+ new Tuple2(c7, "c7_feature")
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+ );
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+ for (Tuple2 tuple2 : tmpList0) {
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+ for (String key_time : Arrays.asList("tags_1d", "tags_3d", "tags_7d")) {
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+ String tags = tuple2.first.getOrDefault(key_time, "");
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+ if (!tags.isEmpty()) {
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+ c34567Map.put(tuple2.name + "_" + key_time, tags);
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+ }
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+ }
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+ }
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+
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+ Map<String, Map<String, String[]>> c89Map = new HashMap<>(4);
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+ List<Tuple2> tmpList1 = Arrays.asList(
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+ new Tuple2(c8, "c8_feature"),
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+ new Tuple2(c9, "c9_feature")
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+ );
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+ for (Tuple2 tuple2 : tmpList1) {
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+ for (String key_action : Arrays.asList("share", "return")) {
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+ String cfListStr = tuple2.first.getOrDefault(key_action, "");
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+ if (!cfListStr.isEmpty()) {
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+ Map<String, String[]> cfMap = new HashMap<>();
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+ String[] entries = cfListStr.split(",");
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+ for (String entry : entries) {
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+ String[] rList = entry.split(":");
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+ if (rList.length >= 4) { // 确保分割后有四个元素
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+ String key = rList[0];
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+ String value1 = rList[1];
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+ String value2 = rList[2];
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+ String value3 = rList[3];
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+ String[] strs = {value1, value2, value3};
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+ cfMap.put(key, strs);
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+ }
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}
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- return resort(scoreKey, result);
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+ c89Map.put(tuple2.name + "_" + key_action, cfMap);
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}
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- } catch (Exception e) {
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- log.error("diversity resort error", e);
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}
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}
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- return result;
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- }
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- private List<Video> resort(String scoreKey, List<Video> videos) {
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- Map<Long, Video> videoMap = new HashMap<>();
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- List<Pair<Long, Double>> list = new ArrayList<>();
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- for (Video video : videos) {
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- long vid = video.getVideoId();
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- videoMap.put(vid, video);
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- Map<String, Double> scoreMap = video.getScoresMap();
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- list.add(Pair.create(vid, scoreMap.getOrDefault(scoreKey, 0d)));
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+ List<RankItem> rankItems = CommonCollectionUtils.toList(rovRecallRank, RankItem::new);
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+ for (RankItem item : rankItems) {
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+ Map<String, Double> featureMap = new HashMap<>();
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+ String vid = item.getVideoId() + "";
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+ Map<String, String> b1 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_all_exp_v2", new HashMap<>());
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+ Map<String, String> b2 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_all_share", new HashMap<>());
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+ Map<String, String> b3 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_all_return", new HashMap<>());
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+ Map<String, String> b6 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_exp2share_v2", new HashMap<>());
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+ Map<String, String> b7 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_share2return", new HashMap<>());
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+
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+ Map<String, String> b8 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_noflow_exp_v2", new HashMap<>());
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+ Map<String, String> b9 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_noflow_root_share_v2", new HashMap<>());
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+ Map<String, String> b10 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_noflow_root_return_v2", new HashMap<>());
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+ Map<String, String> b11 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_flow_exp_v2", new HashMap<>());
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+ Map<String, String> b12 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_flow_root_share_v2", new HashMap<>());
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+ Map<String, String> b13 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_flow_root_return_v2", new HashMap<>());
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+ Map<String, String> b17 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_province_exp_v2", new HashMap<>());
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+ Map<String, String> b18 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_province_root_share_v2", new HashMap<>());
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+ Map<String, String> b19 = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_feed_province_root_return_v2", new HashMap<>());
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+
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+ List<Tuple4> originData = Arrays.asList(
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+ new Tuple4(b1, b2, b3, "b123"),
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+ new Tuple4(b1, b6, b7, "b167"),
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+ new Tuple4(b8, b9, b10, "b8910"),
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+ new Tuple4(b11, b12, b13, "b111213"),
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+ new Tuple4(b17, b18, b19, "b171819")
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+ );
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+
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+ for (Tuple4 tuple4 : originData) {
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+ for (String prefix2 : Arrays.asList("1h", "2h", "3h", "4h", "12h", "1d", "3d", "7d")) {
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+ double exp = tuple4.first.isEmpty() ? 0 : Double.parseDouble(tuple4.first.getOrDefault("exp_pv_" + prefix2, "0.0"));
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+ double share = tuple4.second.isEmpty() ? 0 : Double.parseDouble(tuple4.second.getOrDefault("share_pv_" + prefix2, "0.0"));
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+ double returns = tuple4.third.isEmpty() ? 0 : Double.parseDouble(tuple4.third.getOrDefault("return_uv_" + prefix2, "0.0"));
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+
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+ double f1 = ExtractorUtils.calDiv(share, exp);
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+ double f2 = ExtractorUtils.calLog(share);
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+ double f3 = ExtractorUtils.calDiv(returns, exp);
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+ double f4 = ExtractorUtils.calLog(returns);
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+ double f5 = f3 * f4;
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+
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+ String key1 = tuple4.name + "_" + prefix2 + "_" + "STR";
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+ String key2 = tuple4.name + "_" + prefix2 + "_" + "log(share)";
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+ String key3 = tuple4.name + "_" + prefix2 + "_" + "ROV";
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+ String key4 = tuple4.name + "_" + prefix2 + "_" + "log(return)";
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+ String key5 = tuple4.name + "_" + prefix2 + "_" + "ROV*log(return)";
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+
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+ featureMap.put(key1, f1);
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+ featureMap.put(key2, f2);
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+ featureMap.put(key3, f3);
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+ featureMap.put(key4, f4);
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+ featureMap.put(key5, f5);
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+ }
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+ }
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+
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+ Map<String, String> videoInfo = featureOriginVideo.getOrDefault(vid, new HashMap<>()).getOrDefault("alg_vid_feature_basic_info", new HashMap<>());
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+ featureMap.put("total_time", Double.parseDouble(videoInfo.getOrDefault("total_time", "0")));
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+ featureMap.put("bit_rate", Double.parseDouble(videoInfo.getOrDefault("bit_rate", "0")));
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+
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+ String title = videoInfo.getOrDefault("title", "");
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+ if (!title.isEmpty()) {
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+ List<Future<Pair<String, Double[]>>> futures = new ArrayList<>();
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+ for (String name : Arrays.asList("c3_feature", "c4_feature", "c5_feature", "c6_feature", "c7_feature")) {
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+ for (String key_time : Arrays.asList("tags_1d", "tags_3d", "tags_7d")) {
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+ String key = name + "_" + key_time;
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+ String tags = c34567Map.getOrDefault(key, "");
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+ if (!tags.isEmpty()) {
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+ Future<Pair<String, Double[]>> future = ThreadPoolFactory.defaultPool().submit(() -> {
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+ Double[] doubles = ExtractorUtils.funcC34567ForTagsNew(tags, title);
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+ return Pair.create(key, doubles);
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+ });
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+ futures.add(future);
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+ }
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+ }
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+ }
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+ try {
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+ for (Future<Pair<String, Double[]>> future : futures) {
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+ Pair<String, Double[]> pair = future.get(1000, TimeUnit.MILLISECONDS);
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+ featureMap.put(pair.getFirst() + "_matchnum", pair.getSecond()[0]);
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+ featureMap.put(pair.getFirst() + "_maxscore", pair.getSecond()[1]);
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+ featureMap.put(pair.getFirst() + "_avgscore", pair.getSecond()[2]);
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+ }
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+ } catch (Exception e) {
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+ log.error("concurrent similarity error", e);
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+ }
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+ }
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+
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+ if (!vid.isEmpty()) {
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+ for (String key_feature : Arrays.asList("c8_feature", "c9_feature")) {
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+ for (String key_action : Arrays.asList("share", "return")) {
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+ 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;
|
|
|
+ }
|
|
|
+
|
|
|
+ // 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));
|
|
|
+ }
|
|
|
}
|
|
|
- list.sort(Comparator.comparingDouble(o -> -o.getSecond()));
|
|
|
- return fillVideo(list, videoMap);
|
|
|
- }
|
|
|
+ for (RankItem item : rankItems) {
|
|
|
+ Map<String, String> featureMap = new HashMap<>();
|
|
|
+ Map<String, Double> featureMapDouble = item.featureMapDouble;
|
|
|
+
|
|
|
+ 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
|
|
|
+ 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:vid_hasreturn_vor:");
|
|
|
+
|
|
|
+ // Ros增强传播因子
|
|
|
+ Map<String, Map<String, String>> rosSpreadDivMap = this.getVideoRedisFeature(vids, "vid_for_spread:");
|
|
|
|
|
|
- private List<Video> fillVideo(List<Pair<Long, Double>> list, Map<Long, Video> videoMap) {
|
|
|
List<Video> result = new ArrayList<>();
|
|
|
- for (Pair<Long, Double> pair : list) {
|
|
|
- Video video = videoMap.get(pair.getFirst());
|
|
|
+
|
|
|
+ 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 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);
|
|
|
+ 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());
|
|
|
+ video.setAllFeatureMap(item.getAllFeatureMap());
|
|
|
+ if (MapUtils.isNotEmpty(feature.getVideoFeature()) && MapUtils.isNotEmpty(feature.getVideoFeature().get(item.getVideoId() + ""))) {
|
|
|
+ video.getMetaFeatureMap().putAll(feature.getVideoFeature().get(item.getVideoId() + ""));
|
|
|
+ }
|
|
|
+ if (MapUtils.isNotEmpty(feature.getUserFeature())) {
|
|
|
+ video.getMetaFeatureMap().putAll(feature.getUserFeature());
|
|
|
+ }
|
|
|
result.add(video);
|
|
|
}
|
|
|
+ result.sort(Comparator.comparingDouble(o -> -o.getSortScore()));
|
|
|
return result;
|
|
|
}
|
|
|
+
|
|
|
+ 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";
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
}
|