活动店铺推荐接口优化

@@ -54,7 +54,15 @@ public class ActivityService {
     }
     }
 
 
     private List<Integer> buildShopIds(List<ActivityShopBrand> shopBrandList, UserPersonalFactorRspNew userPersonalFactorRspNew) {
     private List<Integer> buildShopIds(List<ActivityShopBrand> shopBrandList, UserPersonalFactorRspNew userPersonalFactorRspNew) {
-        //1、计算店铺得分
+        //1、获取品牌-店铺的对应关系
+        Map<Integer, Integer> brandId2ShopIdMap = new HashMap<>();
+        for (ActivityShopBrand activityShopBrand : shopBrandList) {
+            brandId2ShopIdMap.put(activityShopBrand.getBrandId(), activityShopBrand.getShopId());
+        }
+        //2、获取实时推荐的品牌
+        List<Integer> recBrandIds = this.getRecBrandIds(userPersonalFactorRspNew);
+
+        //3、计算店铺得分并排序
         List<Double> brandVector = userPersonalFactorRspNew.getBrandVector();
         List<Double> brandVector = userPersonalFactorRspNew.getBrandVector();
         List<Double> brandVectorW2v = userPersonalFactorRspNew.getBrandVectorW2v();
         List<Double> brandVectorW2v = userPersonalFactorRspNew.getBrandVectorW2v();
         if (brandVectorW2v != null && !brandVectorW2v.isEmpty()) {
         if (brandVectorW2v != null && !brandVectorW2v.isEmpty()) {
@@ -62,23 +70,28 @@ public class ActivityService {
         } else {
         } else {
             this.calScore(shopBrandList, brandVectorW2v, true);
             this.calScore(shopBrandList, brandVectorW2v, true);
         }
         }
-        //2、实时推荐店铺加分
-        List<Integer> recBrandIds = this.getRecBrandIds(userPersonalFactorRspNew);
-        for (ActivityShopBrand shopBrand : shopBrandList) {
-            if (recBrandIds.contains(shopBrand.getBrandId())) {
-                shopBrand.setScore(shopBrand.getScore()+100);
-            }
-        }
-        //3、按得分排序
         Collections.sort(shopBrandList, (o1, o2) -> (o2.getScore()).compareTo(o1.getScore()));
         Collections.sort(shopBrandList, (o1, o2) -> (o2.getScore()).compareTo(o1.getScore()));
+
         //4、截取shopId
         //4、截取shopId
         List<Integer> shopIds = new ArrayList<>();
         List<Integer> shopIds = new ArrayList<>();
+
+        //4.1、先获取推荐品牌对应的店铺
+        for (Integer brandId : recBrandIds) {
+            Integer shopId = brandId2ShopIdMap.get(brandId);
+            if (shopId == null || shopIds.contains(shopId)) {
+                continue;
+            }
+            shopIds.add(shopId);
+        }
+        //4.2、再按向量得分排序补满50个
         for (ActivityShopBrand shopBrand : shopBrandList) {
         for (ActivityShopBrand shopBrand : shopBrandList) {
             if (shopIds.size() >= 50) {
             if (shopIds.size() >= 50) {
                 break;
                 break;
             }
             }
+            if (!shopIds.contains(shopBrand.getShopId())) {
                 shopIds.add(shopBrand.getShopId());
                 shopIds.add(shopBrand.getShopId());
             }
             }
+        }
         return shopIds;
         return shopIds;
     }
     }
 
 
@@ -101,7 +114,7 @@ public class ActivityService {
      * 按向量计算品牌得分
      * 按向量计算品牌得分
      */
      */
     private void calScore(List<ActivityShopBrand> shopBrandList, List<Double> userBrandVector, boolean isRnn) {
     private void calScore(List<ActivityShopBrand> shopBrandList, List<Double> userBrandVector, boolean isRnn) {
-        if(userBrandVector==null || userBrandVector.isEmpty()){
+        if (userBrandVector == null || userBrandVector.isEmpty()) {
             return;
             return;
         }
         }
         double userBrandVectorNorm = Word2VectorCalculator.getVectorListNorm(userBrandVector);
         double userBrandVectorNorm = Word2VectorCalculator.getVectorListNorm(userBrandVector);