Title: Community structure detection algorithm based on link prediction

Authors: Gang Dai; Quanxin Wang; Baomin Xu; Lijun Sun

Addresses: School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China; China University of Petroleum-Beijing at Karamay, No. 355 Anding Road, Karamay District, Karamay City, Xinjiang, China ' School of Computer Science, Beijing Jiaotong University Haibin College, Huanghua, China ' School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China ' Key Laboratory of Grain Information Processing and Control, Ministry of Education, Henan University of Technology, Zhengzhou, China; College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China

Abstract: Community structure identification has received a great effort among computer scientists who are focusing on the properties of complex networks. The label propagation algorithm is a near linear time algorithm to find a good community structure. Despite various subsequent advances, an important issue of this algorithm is the efficiency and accuracy of the identified community structure. In this paper, we propose a novel community detection algorithm by using link prediction algorithm based on label propagation. The method is the first to introduce the idea of link prediction into community detection. The experimental results show that the proposed method is less resolution limited than modularity optimising methods, and it can be more effective in detecting communities.

Keywords: complex networks; link prediction; label propagation; community detection.

DOI: 10.1504/IJICT.2021.118577

International Journal of Information and Communication Technology, 2021 Vol.19 No.4, pp.432 - 448

Received: 20 Nov 2019
Accepted: 17 May 2020

Published online: 29 Oct 2021 *

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