Journal
SCIENCE CHINA-INFORMATION SCIENCES
Volume 58, Issue 1, Pages -Publisher
SCIENCE PRESS
DOI: 10.1007/s11432-014-5237-y
Keywords
social network; link prediction; dynamic network; similarity metric; learning model
Funding
- National Key Basic Research and Development Program of China [2014CB340702]
- National Natural Science Foundation of China [61170071, 91318301, 61321491, 61472077]
- China Postdoctoral Science Foundation [2014M560378]
- Foundation of the State Key Laboratory of Software Engineering (SKLSE)
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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 of some active research groups are introduced. Finally, some future challenges of the link prediction in social networks are discussed.
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