优化推荐系数

community-api/src/main/java/com/tanpu/community/api/beans/qo/ThemeAnalysDO.java

@@ -50,11 +50,23 @@ public class ThemeAnalysDO {
     private Double userWeight = 0.0;
 
     public Double getRank() {
+
+        double viewRatio = 0.1;
+        double forwardRatio = 3;
+        double commentRatio = 2;
+        double likeRation = 1;
+        double collectRatio = 3;
+        double userWeightRatio = 0.8;
+        double initialWeight = 1.0;
+        double timeRation = 0.3;
+
         // 质量=帖子质量+用户质量
-        double w = (double) (viewCount * 0.1 + forwardCount * 3 + commentCount * 2 + likeCount * 1 + collectCount * 3) + userWeight;
-        double i = 1; // 初始权重
+        double w = viewCount * viewRatio + forwardCount * forwardRatio + commentCount * commentRatio
+                + likeCount * likeRation + collectCount * collectRatio
+                + Math.pow(userWeight, userWeightRatio);
+        double i = initialWeight; // 初始权重
         double t = Double.valueOf(minuteTillNow) / 60;
-        double g = 0.1; // 时间系数
+        double g = timeRation; // 时间系数
         return (w + i) / Math.pow(t + 1, g);
     }
 

community-service/src/main/java/com/tanpu/community/manager/ConJobManager.java

@@ -40,10 +40,17 @@ public class ConJobManager {
     /**
      * 定时统计主题、话题排行
      */
-    @Scheduled(cron = "0 */1 * * * ?")
+    @Scheduled(cron = "*/30 * * * * ?")
     public void themeRank() {
         rankService.rankThemes();
         rankService.rankTopics();
+    }
+
+    /**
+     * 定时统计主题、话题排行
+     */
+    @Scheduled(cron = "*/5 * * * * ?")
+    public void getThemeNewest() {
         recommendService.refreshNewestThemes();
     }
 }

community-service/src/main/java/com/tanpu/community/service/RecommendService.java

@@ -129,26 +129,28 @@ public class RecommendService {
             int newTimes = newRatio;
             int recTimes = pythonRatio;
             String id;
-            while (hotTimes > 0 && hotThemeIds.size() > hotIdx) {
-                id = hotThemeIds.get(hotIdx);
+            while (newTimes > 0 && newThemeIds.size() > newIdx) {
+                id = newThemeIds.get(newIdx);
                 if (!set.contains(id)) {
                     result.add(id);
                     set.add(id);
                 }
 
-                hotIdx++;
-                hotTimes--;
+                newIdx++;
+                newTimes--;
             }
-            while (newTimes > 0 && newThemeIds.size() > newIdx) {
-                id = newThemeIds.get(newIdx);
+
+            while (hotTimes > 0 && hotThemeIds.size() > hotIdx) {
+                id = hotThemeIds.get(hotIdx);
                 if (!set.contains(id)) {
                     result.add(id);
                     set.add(id);
                 }
 
-                newIdx++;
-                newTimes--;
+                hotIdx++;
+                hotTimes--;
             }
+
             while (recTimes > 0 && recThemeIds.size() > recIdx) {
                 id = recThemeIds.get(recIdx);
                 if (!set.contains(id)) {
@@ -170,15 +172,14 @@ public class RecommendService {
 
         int round = 0;
         while (true) {
-            int hotStart = round * 6;
-            int newestStart = round * 3;
+            int hotStart = round * 3;
+            int newestStart = round * 6;
             int recmdStart = round;
             if (hotStart >= hotIds.size() && newestStart >= newestIds.size() && recmdStart >= recmdIds.size()) {
                 break;
             }
-
-            retList.addAll(BizUtils.subList(hotIds, hotStart, hotStart + 6));
             retList.addAll(BizUtils.subList(newestIds, newestStart, newestStart + 3));
+            retList.addAll(BizUtils.subList(hotIds, hotStart, hotStart + 6));
             retList.addAll(BizUtils.subList(recmdIds, recmdStart, recmdStart + 1));
 
             round++;