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A Bayesian Method for Link Prediction with Considering Path Information

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, ISSN: 1867-8211, Vol: 294 LNCIST, Page: 361-374
2019
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Conference Paper Description

Predicting links among nodes in the network is an interesting and practical problem. Many link prediction methods based on local or global topology alone have been proposed. There is a need to combine these two types of methods to further improve the prediction performance. In line with this direction, we study the link prediction problem based on the Bayesian method and propose a new link prediction method, i.e., path-based Bayesian (PB) method. In this prediction method, we give the definition of clustering coefficients of paths and use it to quantify the contribution of paths to link generation. Then, we propose a new link prediction method by combining the clustering coefficient of paths and Bayesian theory. Simulation results on real-world networks show that our prediction method has higher prediction accuracy than the mainstream methods.

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