2025-04-15 冷启动晋级优化

long-article-recommend-service/src/main/java/com/tzld/longarticle/recommend/server/service/recommend/ArticlePromotionService.java

@@ -97,38 +97,37 @@ public class ArticlePromotionService {
     @Value("${topProducePlanId:}")
     private String topProducePlanId;
 
-    public static boolean abZTestCorrected(double readAvg, int fansA, double viewCount, int fansB, double confidence) {
-        // 检查基础参数合法性
+    /**
+     *
+     * @param readAvg：对照组分子
+     * @param fansA：对照组分母
+     * @param viewCount： 实验组分子
+     * @param fansB: 实验组分母
+     * @param confidence=0.95
+     * @return boolean
+     */
+    public static boolean isExperimentGroupSuperior(double readAvg, int fansA, double viewCount, int fansB, double confidence) {
+
         if (fansA <= 0 || fansB <= 0) {
             throw new IllegalArgumentException("样本量必须大于零");
         }
         if (confidence <= 0 || confidence >= 1) {
             throw new IllegalArgumentException("置信水平必须在 (0,1) 区间");
         }
+        double pA = readAvg / fansA;
+        double pB = viewCount / fansB;
 
-        // 计算比例 (使用浮点除法)
-        double pA = (double) readAvg / fansA;
-        double pB = (double) viewCount / fansB;
-
-        // 防止除零错误
         if (pA <= 0) {
             throw new IllegalArgumentException("A组比例必须大于零");
         }
-
-        // 计算合并方差
         double varA = pA * (1 - pA) / fansA;
         double varB = pB * (1 - pB) / fansB;
         double se = Math.sqrt(varA + varB);
 
-        // 计算Z阈值 (双尾检验)
         NormalDistribution normal = new NormalDistribution();
         double alpha = (1 - confidence) / 2;
         double zThreshold = normal.inverseCumulativeProbability(1 - alpha);
-
-        // 计算置信区间下限
         double ciLow = (pB - pA - zThreshold * se) / pA;
-
-        // 判断是否拒绝原假设
         return ciLow > 0;
     }
 
@@ -150,7 +149,7 @@ public class ArticlePromotionService {
             List<DatastatSortStrategy> listStrategy2 = list.stream()
                     .filter(o -> {
                         try {
-                            return abZTestCorrected(o.getAvgViewCount() * 1.1 * 30, o.getFans() * 30,
+                            return isExperimentGroupSuperior(o.getAvgViewCount() * 1.1 * 30, o.getFans() * 30,
                                     o.getViewCount(), o.getFans(), 0.95);
                         }
                         catch (Exception e) {