摘要
[目的 /意义]利用三度影响力理论,从网络结构的角度进一步拓展用户关系连接,提高社交网络好友推荐的效率。[方法 /过程]首先,计算用户之间的关系强度,并筛选关系强度较大的用户集合;然后,通过用户共同关注的内容计算用户兴趣相似度;最后,融合用户关系强度和兴趣相似度实现好友的推荐并通过实际数据对所提方法进行实证检验。[结果/结论]实验结果表明,融合关系强度和兴趣的社交网络好友推荐方法具有较好的效果,可为用户推荐提供参考和借鉴。该方法进一步完善社会化推荐理论。
[ Purpose/significance] Aiming at improving the efficiency of friend recommendation algorithm ,this paper expands the connecting relations between social network users based on the theory of three-degree influence. [ Method/ process] Firstly, the strength of friend relationships between users could be calculated, which would be used to filter out user set. Secondly, this paper calculates the similarity of interests based on the content of common concern of users. Thirdly, it achieved to recommend friends to social network users by fusing the strength of relationships and the similarity of interests. [ Result/conclusion] The experiment results on douban data show that the proposed method is a better recommendation method. It can be helpful for the friend recommendation and complements the theory of social recommendation.
出处
《图书情报工作》
CSSCI
北大核心
2017年第1期64-71,共8页
Library and Information Service
基金
国家社会科学基金重大项目“基于多维度聚合的网络资源知识发现研究”(项目编号:13&ZD183)
国家社会科学基金项目“基于关联数据的数字图书馆多粒度集成知识服务研究”(项目编号:14CTQ003)研究成果之一
关键词
三度影响力
关系强度
兴趣相似度
好友推荐
three-degree influence relationship strength interest similarity friend recommendation