Merge branch 'yxh/0912' of Server/long-article-recommend into master

long-article-recommend-service/src/main/java/com/tzld/longarticle/recommend/server/service/score/strategy/ViewCountRateCorrelationStrategy.java

@@ -71,7 +71,10 @@ public class ViewCountRateCorrelationStrategy implements ScoreStrategy {
                     if (hisItem.isInnerAccount() && Objects.nonNull(hisItem.getViewCount())
                             && hisItem.getViewCount() > 0 && Objects.nonNull(hisItem.getAvgViewCount())
                             && hisItem.getAvgViewCount() > 0) {
-                        Double correlation = (hisItem.getCorrelation() + 1) / 2;
+                        Double correlation = 0.3D;
+                        if (hisItem.getCorrelation() > 0) {
+                            correlation = (hisItem.getCorrelation() + 1) / 2;
+                        }
                         maxAvgViewCount = Math.max(maxAvgViewCount, hisItem.getAvgViewCount());
                         if (hisItem.getItemIndex() == 1) {
                             showViewCountSumFirst += (hisItem.getViewCount() * correlation);
@@ -83,7 +86,7 @@ public class ViewCountRateCorrelationStrategy implements ScoreStrategy {
                                 if (hisItem.getFirstViewCountRate() > 1) {
                                     // 对于头条均值倍数大于1的情况，次条均值线性增加，用于debias；
                                     // TODO: 对于小于1的情况，是否要减去？
-                                    avgViewCountSumSecond += (hisItem.getAvgViewCount() * correlation) * (hisItem.getFirstViewCountRate() - 1);
+                                    avgViewCountSumSecond += (hisItem.getAvgViewCount() * correlation) * hisItem.getFirstViewCountRate();
                                 } else {
                                     avgViewCountSumSecond += (hisItem.getAvgViewCount() * correlation);
                                 }
@@ -95,7 +98,7 @@ public class ViewCountRateCorrelationStrategy implements ScoreStrategy {
                                 if (hisItem.getFirstViewCountRate() > 1) {
                                     // 对于头条均值倍数大于1的情况，次条均值线性增加，用于debias；
                                     // TODO: 对于小于1的情况，是否要减去？
-                                    avgViewCountSum += (hisItem.getAvgViewCount() * correlation) * (hisItem.getFirstViewCountRate() - 1);
+                                    avgViewCountSum += (hisItem.getAvgViewCount() * correlation) * hisItem.getFirstViewCountRate();
                                 } else {
                                     avgViewCountSum += (hisItem.getAvgViewCount() * correlation);
                                 }

long-article-recommend-service/src/main/java/com/tzld/longarticle/recommend/server/service/score/strategy/ViewCountRateStrategy.java

@@ -82,7 +82,7 @@ public class ViewCountRateStrategy implements ScoreStrategy {
                                 if (hisItem.getFirstViewCountRate() > 1) {
                                     // 对于头条均值倍数大于1的情况，次条均值线性增加，用于debias；
                                     // TODO: 对于小于1的情况，是否要减去？
-                                    avgViewCountSumSecond += hisItem.getAvgViewCount() * (hisItem.getFirstViewCountRate() - 1);
+                                    avgViewCountSumSecond += hisItem.getAvgViewCount() * hisItem.getFirstViewCountRate();
                                 } else {
                                     avgViewCountSumSecond += hisItem.getAvgViewCount();
                                 }
@@ -94,7 +94,7 @@ public class ViewCountRateStrategy implements ScoreStrategy {
                                 if (hisItem.getFirstViewCountRate() > 1) {
                                     // 对于头条均值倍数大于1的情况，次条均值线性增加，用于debias；
                                     // TODO: 对于小于1的情况，是否要减去？
-                                    avgViewCountSum += hisItem.getAvgViewCount() * (hisItem.getFirstViewCountRate() - 1);
+                                    avgViewCountSum += hisItem.getAvgViewCount() * hisItem.getFirstViewCountRate();
                                 } else {
                                     avgViewCountSum += hisItem.getAvgViewCount();
                                 }