Link prediction using node information on local paths

Furqan Aziz, Haji Gul, Ishtiaq Muhammad and Irfan Uddin

Physica A: Statistical Mechanics and its Applications, 2020, vol. 557, issue C

Abstract: Link prediction is one of the most important and challenging tasks in complex network analysis, which aims to predict missing link based on existing ones in a network. This problem is of both theoretical interest and has applications in diverse scientific disciplines, including social network analysis, recommendation systems, and biological networks. In this paper we propose a novel link prediction method that aims at improving the accuracy of existing path-based methods by incorporating information about the nodes along local paths. We investigate the proposed framework empirically and conduct extensive experiments on real-world datasets obtained from diverse domains. Results show that the proposed method has achieved increased prediction accuracy when compared to existing state-of-the-art link prediction methods.

Keywords: Complex networks; Link prediction; Node information (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:557:y:2020:i:c:s0378437120305112

DOI: 10.1016/j.physa.2020.124980

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