基于社交网络和协同过滤的微博好友推荐算法

Recommendation algorithm of microblogging friends based on social networking and collaborative filtering

微博作为近年来用户数量较多的社交应用,其用户的信息压力也相对较大,推荐技术对于微博用户的体验和推广有很明显的帮助.本文将针对微博平台的好友推荐进行研究,分别采用基于社交网络分析和基于协同过滤技术的推荐算法.经过两种算法的实验对比得出结论:基于协同过滤的好友推荐算法具有较好的性能,在推荐好友数量较多的情况下依然具有较高的综合评价指标,提高了好友推荐的质量.

As a social application that has a large number of users in recently years, the informa- tion pressure of microblogging users is relatively powerful. Recommendation technology is helpful to user experience and promotion of microblogging. The paper studies on the friend recommenda- tion on the microblogging platform, and the recommendation algorithms based on social network analysis and collaborative filtering are respectively introduced. After experimental comparison of the two algorithms, it comes to conclusion that friend recommendation algorithm based on col- laborative filtering has better performance and has good evaluation index under the large number of friend recommendation. It also can improve the quality of friend recommendation.