A robust multi-view clustering method for community detection combining link and content information

Chaobo He, Yong Tang, Hai Liu, Xiang Fei, Hanchao Li and Shuangyin Liu

Physica A: Statistical Mechanics and its Applications, 2019, vol. 514, issue C, 396-411

Abstract: Community detection is an important problem of complex networks analysis and various methods have been proposed to solve it. However, most of the existing methods only use the link information. As a result, the quality of their detected communities is often poor due to the sparse and noisy data existing in link information. Actually, content information of complex networks can also help to improve the quality of community detection. In this paper, we propose a method based on Multi-View Clustering via Robust Nonnegative Matrix Factorization (MVCRNMF). This method can provide a unified framework to combine link and content information for community detection. Its key idea is to build a multi-view robust NMF model with the co-regularized constraint on community indicator matrices of link view and content view. This can make link and content information complement each other during the factorization process of NMF. We devise iterative update rules as the optimization solution to the community detection model and also give the rigorous convergence proof. It is worth noting that MVCRNMF can learn the contribution weights from link and content information adaptively and this helps to save a lot of time on tuning the weight parameters. We conduct comparative experiments on four real-world complex networks. The results demonstrate that MVCRNMF performs better than state-of-the-art methods. Additionally, results of the case study on a co-authorship network also show that MVCRNMF can obtain higher quality communities.

Keywords: Community detection; Multi-view clustering; Robust nonnegative matrix factorization; Complex networks (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437118312184
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:514:y:2019:i:c:p:396-411

DOI: 10.1016/j.physa.2018.09.086

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().