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Community Detection in Complex Networks using Link Prediction

2016/11/01 by Huimin Cheng, Yi-Zi Ning, Cheng, Hui-Min +9 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Advanced Graph Neural Networks #Bioinformatics and Genomic Networks #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)

paper · pdf · doi:10.48550/arxiv.1611.00254

openalex publication_date 2016/11/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Community detection and link prediction are both of great significance in network analysis, which provide very valuable insights into topological structures of the network from different perspectives. In this paper, we propose a novel community detection algorithm with inclusion of link prediction, motivated by the question whether link prediction can be devoted to improving the accuracy of community partition. For link prediction, we propose two novel indices to compute the similarity between each pair of nodes, one of which aims to add missing links, and the other tries to remove spurious edges. Extensive experiments are conducted on benchmark data sets, and the results of our proposed algorithm are compared with two classes of baseline. In conclusion, our proposed algorithm is competitive, revealing that link prediction does improve the precision of community detection.

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