Study on Improved Influence Page Rank Algorithm Based On User Behavior

被引：0
|
作者：
Wu, Yun [1 ]
机构：
[1] BaoTou Teachers Coll, Baotou, Peoples R China
来源：
2ND INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND INDUSTRIAL AUTOMATION (ICITIA 2017) | 2017年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
User influence ranking is an important subject of social network research, for public opinion control, important dissemination and so on is a great significance. The traditional PageRank algorithm only considers the relationship between users, this paper combines the Page Rank algorithm with the user behavior, integrates the follower quality, comment rate, forwarding rate and whether the authentication behavior and other user behavior factors, proposed an improved algorithm URank. Experiments based on the SIR propagation model show that the URank algorithm is superior to the PageRank algorithm in calculating the accuracy of the influence index for large-scale data sets.
引用
收藏
页码：361 / 368
页数：8
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