Community Discovery on Multi-View Social Networks via Joint Regularized Nonnegative Matrix Triple Factorization

Liangliang ZHANG  Longqi YANG  Yong GONG  Zhisong PAN  Yanyan ZHANG  Guyu HU  

IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.6   pp.1262-1270
Publication Date: 2017/06/01
Publicized: 2017/03/21
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017EDP7004
Type of Manuscript: PAPER
Category: Artificial Intelligence, Data Mining
data mining,  community discovery,  social network,  nonnegative matrix factorization,  

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In multi-view social networks field, a flexible Nonnegative Matrix Factorization (NMF) based framework is proposed which integrates multi-view relation data and feature data for community discovery. Benefit with a relaxed pairwise regularization and a novel orthogonal regularization, it outperforms the-state-of-art algorithms on five real-world datasets in terms of accuracy and NMI.