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论文类型：期刊论文

发表时间：2013-03-10

发表刊物：MODERN PHYSICS LETTERS B

收录刊物：SCIE

卷号：27

期号：6

ISSN号：0217-9849

关键字：Link prediction; complex network; similarity index

摘要：Link prediction in complex networks has attracted much attention recently. Many local similarity measures based on the measurements of node similarity have been proposed. Among these local similarity indices, the neighborhood-based indices Common Neighbors (CN), Adamic-Adar (AA) and Resource Allocation (RA) index perform best. It is found that the node similarity indices required only information on the nearest neighbors are assigned high scores and have very low computational complexity. In this paper, a new index based on the contribution of common neighbor nodes to edges is proposed and shown to have competitively good or even better prediction than other neighborhood-based indices especially for the network with low clustering coefficient with its high efficiency and simplicity.