modify

linucb/views/linucb.py

@@ -87,10 +87,10 @@ class LinUCB:
                 for top_score_index in np_score_dict[top_score]:
                     tag_id = str(tag_list[top_score_index], encoding="utf-8")
                     top_tag_dict[tag_id] = top_score
-                    if len(top_tag_dict) >= 50:
+                    if len(top_tag_dict) >= 3:
                         break
 
-                if len(top_tag_dict) >= 50:
+                if len(top_tag_dict) >= 3:
                     break
 
             logging.info("duan add,device_id:%s,sorted_np_score_list:%s,np_score_dict:%s" % (str(device_id), str(sorted_np_score_list), str(np_score_dict)))

search/utils/topic.py

@@ -121,7 +121,7 @@ class TopicUtils(object):
 
     @classmethod
     def get_recommend_topic_ids(cls,user_id,tag_id,offset,size,single_size,query=None,query_type=TopicPageType.FIND_PAGE,
-                                filter_topic_id_list=[],test_score=False,must_topic_id_list=[],recommend_tag_dict={},
+                                filter_topic_id_list=[],test_score=False,must_topic_id_list=[],recommend_tag_list=[],
                                 user_similar_score_list=[],index_type="topic"):
         """
         :需增加打散逻辑
@@ -224,14 +224,22 @@ class TopicUtils(object):
                         "weight": 1
                     }
                 )
-            for tag_id in recommend_tag_dict:
+            if len(recommend_tag_list)>0:
                 functions_list.append(
                     {
-                        "filter": {"term": {"tag_list": tag_id}},
-                        "weight": 3+recommend_tag_dict[tag_id]
+                        "filter": {"terms": {"tag_list": recommend_tag_list}},
+                        "weight": 3
                     }
                 )
 
+            # for tag_id in recommend_tag_dict:
+            #     functions_list.append(
+            #         {
+            #             "filter": {"term": {"tag_list": tag_id}},
+            #             "weight": recommend_tag_dict[tag_id]
+            #         }
+            #     )
+
             low_content_level = 4 if query_type == TopicPageType.FIND_PAGE else 3
             query_function_score = {
                 "query": {

search/views/topic.py

@@ -58,10 +58,15 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
         tag_recommend_redis_key = "physical:linucb:tag_recommend:device_id:" + str(device_id)
 
 
-        recommend_tag_dict = dict()
+        # recommend_tag_dict = dict()
+        # tag_recommend_val = redis_client.get(tag_recommend_redis_key)
+        # if tag_recommend_val:
+        #     recommend_tag_dict = json.loads(str(tag_recommend_val, encoding="utf-8"))
+
+        recommend_tag_list = list()
         tag_recommend_val = redis_client.get(tag_recommend_redis_key)
         if tag_recommend_val:
-            recommend_tag_dict = json.loads(str(tag_recommend_val, encoding="utf-8"))
+            recommend_tag_list = json.loads(str(tag_recommend_val, encoding="utf-8"))
 
         recommend_topic_ids = []
         have_read_topic_id_list = list()
@@ -81,7 +86,7 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
         topic_id_list = TopicUtils.get_recommend_topic_ids(user_id=user_id, tag_id=tag_id, offset=offset, size=size,
                                                            single_size=size,query=query, query_type=query_type,
                                                            filter_topic_id_list=have_read_topic_id_list,
-                                                           recommend_tag_dict=recommend_tag_dict,
+                                                           recommend_tag_list=recommend_tag_list,
                                                            user_similar_score_list=user_similar_score_redis_list,index_type="topic-high-star")
         have_read_group_id_set = set()
         have_read_user_id_set = set()