A Link Prediction Model Based on Similarity between Links

Abstract:

With the development of network science, the link prediction problem has attracted more and more attention. Among which, link prediction methods based on similarity has been most widely studied. Previous methods depicting similarity of nodes mainly consider their common neighbors. But in this paper, from the view of network environment of nodes, which is to analysis the links around the pair of nodes, derive nodes similarity through that of links, a new way to solve the link prediction problem is provided. This paper establishes a link prediction model based on similarity between links, presents the LE index. Finally, the LE index is tested on five real datasets, and compared with existing similarity-based link prediction methods, the experimental results show that LE index can achieve good prediction accuracy, especially outperforms the other methods in the Yeast network.

• Periodical: Applied Mechanics and Materials (Volumes 651-653)
• Pages: 1748-1752
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.651-653.1748
• Online since: September 2014
• Authors: Fu Li Xie*, Guang Quan Cheng
• Keywords: Link Prediction, Network, Similarity of Links

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