Topic model based link prediction for directed social network

被引：0

作者：

Wu, Mengdie ^{[1
]}

Tang, Yan ^{[1
]}

机构：

[1] School of Computer and Information Science, Southwest University

来源：

Journal of Computational Information Systems | 2014年 / 10卷 / 11期

关键词：

Link prediction; Social network; Topic model;

D O I：

10.12733/jcis10423

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Link prediction methods for social network are usually designed with single feature for simple networks. They can hardly model the actual situation any longer because social networks are highly dynamic objects. A topic model based link prediction method for directed social network is proposed in this paper. It synthesizes attributes of nodes and network structure for link prediction, and analyses semantic information based on topic model as one of node attributes. Experiment shows that the proposed method can efficiently improve the accuracy of link prediction. © 2014 Binary Information Press.

引用

页码：4765 / 4774

页数：9

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