期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2014
卷号：2014
DOI：10.1155/2014/461780
出版社：Hindawi Publishing Corporation
摘要：In this paper, we investigate how user’s online behavior (e.g., making friendships) and their offline activity (e.g., check-ins) affected each other by leveraging the data collected from LBSN. First, we use vectors to represent nodes and define popularity entropy for each node to weigh their popularities and the impact on forming a new edge. Then, we propose an algorithm to calculate the weight of each edge based on our findings that the more overlap of linked nodes they have, the heavier weight the edge has and the more popular the nodes in their overlap are, the lighter the weight of the edge is. Finally, we conduct link prediction by using the random walk with restart method considering the effect of every node and every edge. Experimental results show that user’s activity in virtual world and physical world do really have great impact on each other.
