A Fusion Link Prediction Method Based on Limit Theorem

The theoretical limit of link prediction is a fundamental problem in this field. Taking the network structure as object to research this problem is the mainstream method. This paper proposes a new viewpoint that link prediction methods can be divided into single or combination methods, based on the...

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Bibliographic Details
Published inApplied sciences Vol. 8; no. 1; p. 32
Main Authors Wu, Yiteng, Yu, Hongtao, Huang, Ruiyang, Li, Yingle, Lin, Senjie
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.01.2018
Subjects
combination method
link prediction
Methods
Probability density functions
theoretical limit
TLF method
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Summary:The theoretical limit of link prediction is a fundamental problem in this field. Taking the network structure as object to research this problem is the mainstream method. This paper proposes a new viewpoint that link prediction methods can be divided into single or combination methods, based on the way they derive the similarity matrix, and investigates whether there a theoretical limit exists for combination methods. We propose and prove necessary and sufficient conditions for the combination method to reach the theoretical limit. The limit theorem reveals the essence of combination method that is to estimate probability density functions of existing links and nonexistent links. Based on limit theorem, a new combination method, theoretical limit fusion (TLF) method, is proposed. Simulations and experiments on real networks demonstrated that TLF method can achieve higher prediction accuracy.
ISSN:2076-3417
2076-3417
DOI:10.3390/app8010032