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Link prediction based on local random walk

Europhysics Letters (EPL) · 2010 · Vol. 89(5) · pp. 58007–58007
Weiping LiuLinyuan Lü

Abstract

The problem of missing link prediction in complex networks has attracted much attention recently. Two difficulties in link prediction are the sparsity and huge size of the target networks. Therefore, the design of an efficient and effective method is of both theoretical interests and practical significance. In this Letter, we proposed a method based on local random walk, which can give competitively good prediction or even better prediction than other random-walk-based methods while has a lower computational complexity.

Complex Network Analysis TechniquesAdvanced Graph Neural NetworksOpinion Dynamics and Social InfluenceRandom walkComputer scienceLink (geometry)Artificial intelligenceMachine learningAlgorithmData miningMathematicsStatistics
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564
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Proceedings of the Royal Society B Biological Sciences · 2001 · 1,046 citations
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American Journal of Sociology · 1987 · 5,123 citations
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American Journal of Sociology · 1973 · 38,010 citations
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