Constrained Symmetric Non-Negative Matrix Factorization with Deep Autoencoders for Community Detection

Wei Zhang, Shanshan Yu (), Ling Wang, Wei Guo and Man-Fai Leung
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Wei Zhang: College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China
Shanshan Yu: Training and Basic Education Management Office, Southwest University, Chongqing 400715, China
Ling Wang: College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China
Wei Guo: College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China
Man-Fai Leung: School of Computing and Information Science, Faculty of Science and Engineering, Anglia Ruskin University, Cambridge CB1 1PT, UK

Mathematics, 2024, vol. 12, issue 10, 1-17

Abstract: Recently, community detection has emerged as a prominent research area in the analysis of complex network structures. Community detection models based on non-negative matrix factorization (NMF) are shallow and fail to fully discover the internal structure of complex networks. Thus, this article introduces a novel constrained symmetric non-negative matrix factorization with deep autoencoders (CSDNMF) as a solution to this issue. The model possesses the following advantages: (1) By integrating a deep autoencoder to discern the latent attributes bridging the original network and community assignments, it adeptly captures hierarchical information. (2) Introducing a graph regularizer facilitates a thorough comprehension of the community structure inherent within the target network. (3) By integrating a symmetry regularizer, the model’s capacity to learn undirected networks is augmented, thereby facilitating the precise detection of symmetry within the target network. The proposed CSDNMF model exhibits superior performance in community detection when compared to state-of-the-art models, as demonstrated by eight experimental results conducted on real-world networks.

Keywords: community detection; undirected network; non-negative matrix factorization; deep learning; symmetry regularization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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