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论文类型：会议论文

发表时间：2016-05-23

收录刊物：EI、CPCI-S

卷号：83

页面范围：82-89

关键字：link prediction; Common Neighbors; dynamic network

摘要：Link prediction is an important issue in social networks. Most of the existing methods aim to predict interactions between individuals for static networks, ignoring the dynamic feature of social networks. This paper proposes a link prediction method which considers the dynamic topology of social networks. Given a snapshot of a social network at time t (or network evolution between t1 and t2), we seek to accurately predict the edges that will be added during the interval from time t (or t2) to a given future time t'. Our approach utilizes three metrics, the time-varied weight, the change degree of common neighbor and the intimacy between common neighbors. Moreover, we redefine the common neighbors by finding them within two hops. Experiments on DBLP show that our method can reach better results. (C) 2016 The Authors. Published by Elsevier B.V.