摘要
对PageRank算法进行了缺陷分析和算法推导,针对社交网络中用户间好友关系的特殊性,结合重启特征和稀疏网络平滑特征,提出了PageRank改进算法——PRS算法。结果证明:PageRank算法倾向于以计算入链数量作为衡量标准,而PRS算法更倾向于综合情况。在社交网络中,PRS算法更适合计算用户影响力大小。
This paper analyzes the defects of PageRank algorithm and derives the algorithm, in view of the particularity of the relationship among the users in the social network, puts forward an improved PageRank algorithm named PRS algorithm based on the characteristics of the restart and the sparse network smoothing. The results show that the PageRank algorithm tends to calculate the number of incoming links as a measure, and the PRS algorithm is more prone to comprehensive situation. In the social network, PRS algorithm is more suitable for calculating the size of the user influence.
出处
《图书情报导刊》
2017年第4期74-78,共5页
Journal of Library and Information Science
