摘要
以微博用户推荐算法中相似度计算为研究对象,根据微博用户关注信息的特点,分析了关注用户的流行度的不同程度,以及这种程度差异对相似度计算产生的影响,在此基础之上提出了一种加入流行度制衡因子的相似度计算方法.可通过流行度制衡因子,在计算用户相似度时,适度减少(增加)流行度偏高(偏低)的用户对计算结果的影响.实验结果表明:加入流行度制衡因子的用户相似度计算具有更好的推荐效果.
This paper aims to improve the performance of micro-blog users′recommendation algorithm whose key issue is user similarity calculation .This paper firstly introduces current several user similarity calculation methods and their shortcomings.And then, based on the characteristics of micro-blog users, we discuss their concerning users′popularity of different level , which aims to explore their effects on the user similarity calculation .And on this basis , an improved similarity calculating method of considering depression factor is proposed .In the user similarity calculation , popularity balance factor can reduce/increase the impact of calculation results caused by the user high/low popularity . The experimental results indicate that the proposed user similarity calculation method has better recommendation results .
出处
《中南民族大学学报（自然科学版）》
CAS
北大核心
2015年第3期88-94,共7页
Journal of South-Central University for Nationalities：Natural Science Edition
基金
湖北省自然科学基金资助项目(2011CDB416)
关键词
微博
个性化推荐
用户相似度
流行度制衡
micro-blog
personalized recommendation
user similarity
popularity depression
