%0 Journal Article
%T 基于关联规则和多特征模型的微博好友推荐算法<br>Microblog Friend Recommendation Algorithm Based on Association Rules and Multi Feature Model
%A 丁舟
%A 胡建成
%J Advances in Applied Mathematics
%P 3412-3420
%@ 2324-8009
%D 2021
%I Hans Publishing
%R 10.12677/AAM.2021.1010359
%X 本文通过爬虫程序从新浪微博获得用户的个人信息、关注/粉丝列表信息和微博正文信息等，然后通过分析数据，基于用户社交相似度、用户兴趣相似度、用户间的地理相似度和用户影响力等因素向目标用户进行好友推荐。此外，还利用非目标用户的关注信息，采用关联规则分析技术，为目标用户推荐感兴趣的博主。本文采用的推荐策略经过数据验证，效果良好。<br />
This paper obtains the user’s personal information, attention/fan list information and microblog text information from Sina Weibo through the crawler program, and then recommends friends to the target users based on the user’s social similarity, user interest similarity, geographical similarity between users and user influence by analyzing the data. In addition, it also uses the attention information of non target users and association rule analysis technology to recommend interested bloggers for target users. The recommendation strategy used in this paper is verified by data and has good effect.
%K 微博，好友推荐，关联规则，社交网络，数据挖掘<br>Microblog
%K Recommended by Friends
%K Association Rules
%K Social Networks
%K Data Mining
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=45948