基于关联规则与标签的好友推荐算法

J4 ›› 2013, Vol. 35 ›› Issue (2): 109-113.

基于关联规则与标签的好友推荐算法

胡文江，胡大伟，高永兵，郝斌

（内蒙古科技大学信息工程学院,内蒙古包头 014010）

收稿日期:2012-03-08 修回日期:2012-06-16 出版日期:2013-02-25 发布日期:2013-02-25
基金资助:
教育部春晖计划资助项目 (00110310)

Friend recommendation algorithm based on association rules and tags

HU Wenjiang,HU Dawei,GAO Yongbing,HAO Bin

(School of Information Engineering,Inner Mongolia University of Science and Technology,Baotou 014010,China)

Received:2012-03-08 Revised:2012-06-16 Online:2013-02-25 Published:2013-02-25

摘要/Abstract

摘要：

针对用户在社交网络中添加哪些用户为自己好友的问题，采用好友之间的关系推荐和喜好标签的相似度推荐相结合的方法,提出了改进的推荐算法。首先,通过用户之间的好友关系推荐出目标用户共同好友最多的TopN用户，其次,通过目标用户和推荐出的TopN用户间标签的相似性推荐分数最高的用户，再给定他们相应的权重，进行打分，选取分数最高的TopN用户进行推荐。实验结果表明，运用相结合的算法是有效的，在准确率和召回率上优于同类的好友推荐算法。

关键词: 关联规则；好友推荐；标签；相似性

Abstract:

The paper proposes an improved friend recommendation algorithm in social networks. It combines the relationship recommendation among friends and the similarity recommendation of tags. Firstly, through the friend relationship, the TopN common friends among the target users are recommended. Secondly, the tag similarity among the target users and the recommended TopN friends is used to recommend the friends with the highest similarity score, and they are given corresponding weights and scored. Finally, the TopN uses with the highest scores are recommended. The results show that the proposed improved algorithm is efficient and its precision and recall rates are better than the common friend recommendation algorithms.

Key words: association rules;friendly recommendation;tag；similarity

胡文江，胡大伟，高永兵，郝斌. 基于关联规则与标签的好友推荐算法[J]. J4, 2013, 35(2): 109-113.

HU Wenjiang,HU Dawei,GAO Yongbing,HAO Bin. Friend recommendation algorithm based on association rules and tags[J]. J4, 2013, 35(2): 109-113.