publication . Article . Other literature type . Preprint . 2014

Link prediction in social networks: the state-of-the-art

Wang, Peng; Xu, Baowen; Wu, Yurong; Zhou, Xiaoyu;
Open Access
  • Published: 03 Dec 2014 Journal: Science China Information Sciences, volume 58, pages 1-38 (issn: 1674-733X, eissn: 1869-1919, Copyright policy)
  • Publisher: Springer Science and Business Media LLC
Abstract
In social networks, link prediction predicts missing links in current networks and new or dissolution links in future networks, is important for mining and analyzing the evolution of social networks. In the past decade, many works have been done about the link prediction in social networks. The goal of this paper is to comprehensively review, analyze and discuss the state-of-the-art of the link prediction in social networks. A systematical category for link prediction techniques and problems is presented. Then link prediction techniques and problems are analyzed and discussed. Typical applications of link prediction are also addressed. Achievements and roadmaps ...
Subjects
free text keywords: Artificial intelligence, business.industry, business, Dynamic network analysis, Mathematics, Mathematical optimization, Social network, Computer Science - Social and Information Networks, Physics - Physics and Society
Related Organizations
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publication . Article . Other literature type . Preprint . 2014

Link prediction in social networks: the state-of-the-art

Wang, Peng; Xu, Baowen; Wu, Yurong; Zhou, Xiaoyu;