Detecting Communities in 2-Mode Networks via Fast Nonnegative Matrix Trifactorization
Joint Authors
Yang, Liu
Xin-sheng, Ji
Caixia, Liu
Tao, Wang
Mingyan, Xu
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-02
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
With the rapid development of the Internet and communication technologies, a large number of multitype relational networks widely emerge in real world applications.
The bipartite network is one representative and important kind of complex networks.
Detecting community structure in bipartite networks is crucial to obtain a better understanding of the network structures and functions.
Traditional nonnegative matrix factorization methods usually focus on homogeneous networks, and they are subject to several problems such as slow convergence and large computation.
It is challenging to effectively integrate the network information of multiple dimensions in order to discover the hidden community structure underlying heterogeneous interactions.
In this work, we present a novel fast nonnegative matrix trifactorization (F-NMTF) method to cocluster the 2-mode nodes in bipartite networks.
By constructing the affinity matrices of 2-mode nodes as manifold regularizations of NMTF, we manage to incorporate the intratype and intratype information of 2-mode nodes to reveal the latent community structure in bipartite networks.
Moreover, we decompose the NMTF problem into two subproblems, which are involved with much less matrix multiplications and achieve faster convergence.
Experimental results on synthetic and real bipartite networks show that the proposed method improves the slow convergence of NMTF and achieves high accuracy and stability on the results of community detection.
American Psychological Association (APA)
Yang, Liu& Tao, Wang& Xin-sheng, Ji& Caixia, Liu& Mingyan, Xu. 2015. Detecting Communities in 2-Mode Networks via Fast Nonnegative Matrix Trifactorization. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1075107
Modern Language Association (MLA)
Yang, Liu…[et al.]. Detecting Communities in 2-Mode Networks via Fast Nonnegative Matrix Trifactorization. Mathematical Problems in Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1075107
American Medical Association (AMA)
Yang, Liu& Tao, Wang& Xin-sheng, Ji& Caixia, Liu& Mingyan, Xu. Detecting Communities in 2-Mode Networks via Fast Nonnegative Matrix Trifactorization. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1075107
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1075107