Computer Science ›› 2017, Vol. 44 ›› Issue (10): 96-98.doi: 10.11896/j.issn.1002-137X.2017.10.018

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Improved Link Prediction Method for Weighted Networks

CHEN Xu and CHEN Ke-jia   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Currently,link mining in complex networks has been extensively studied.However,there are only a few rela-ted works on weighted networks and the results are not satisfactory.A new link prediction method for weighted networks was proposed by improving the weighted similarity measure of network structure.The new method is based on the assumption that when the link xz is strong and the link zy is weak,the link 〈x,z,y〉 has the least contribution to the link between node x and y.Therefore,in the new method,as the link xz is strong and the link zy is weak,the degree of weakening of the link 〈x,z,y〉 to the contribution degree of the similarity score S(x,y) between the node x and y is maximal.Comparative experiments on weighted dataset USAir and NetScience show that the proposed method has better performance in AUC indicators.

Key words: Weighted complex networks,Link prediction,Similarity index,Weak ties theory

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