模型实验

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

@@ -44,7 +44,7 @@ public class RankService {
     @Autowired
     public RedisTemplate<String, String> redisTemplate;
     @Autowired
-    public FeatureRemoteService featureRemoteService;
+    private FeatureRemoteService featureRemoteService;
     @Value("${newRankSwitch:false}")
     private boolean newRankSwitch;
     @Value("${newRankAbExpCode:528}")

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4Density.java

@@ -21,7 +21,8 @@ import java.util.*;
 import java.util.stream.Collectors;
 
 /**
- * @author dyp
+ * @author zhangbo
+ * @desc 带密度控制的后处理 排序实验
  */
 @Service
 @Slf4j

recommend-server-service/src/main/java/com/tzld/piaoquan/recommend/server/service/rank/strategy/RankStrategy4RankModel.java

@@ -26,7 +26,8 @@ import java.util.*;
 import java.util.stream.Collectors;
 
 /**
- * @author dyp
+ * @author zhangbo
+ * @desc 模型的排序实验
  */
 @Service
 @Slf4j
@@ -63,7 +64,7 @@ public class RankStrategy4RankModel extends RankService {
         List<String> videoIdKeys = rovRecallRank.stream()
                 .map(t -> param.getRankKeyPrefix() + t.getVideoId())
                 .collect(Collectors.toList());
-        List<String> videoScores = redisTemplate.opsForValue().multiGet(videoIdKeys);
+        List<String> videoScores = this.redisTemplate.opsForValue().multiGet(videoIdKeys);
         log.info("rank mergeAndRankRovRecall videoIdKeys={}, videoScores={}", JSONUtils.toJson(videoIdKeys),
                 JSONUtils.toJson(videoScores));
         if (CollectionUtils.isNotEmpty(videoScores)