Title
Overlapping community detection with preference and locality information: a non-negative matrix factorization approach.
Abstract
Community detection plays an important role in understanding structures and patterns in complex networks. In real-world networks, a node in most cases belongs to multiple communities, which makes communities overlap with each other. One popular technique to cope with overlapping community detection is matrix factorization (MF). However, existing MF approaches only make use of the existence of a link, but ignore the implicit preference information inside it. In this paper, we first propose a Preference-based Non-negative Matrix Factorization (PNMF) model to take link preference information into consideration. Distinguished from traditional value approximation-based matrix factorization approaches, our model maximizes the likelihood of the preference order for each node so that it overcomes the indiscriminate penalty problem in which non-linked pairs inside one community are equally penalized in objective functions as those across two communities. Moreover, we propose a Locality-based Non-negative Matrix Factorization (LNMF) model to further incorporate the concept of locality and generalize the preference system of PNMF. Particularly, we define a subgraph called “K-degree local network” to set a boundary between local non-neighbors and other non-neighbors, and explicitly treat these two classes of non-neighbors in objective function. Through experiments on various benchmark networks, we show that our PNMF model outperforms state-of-the-art baselines, and the generalized LNMF model further performs better than the PNMF model on datasets with high locality.
Year
DOI
Venue
2018
10.1007/s13278-018-0521-2
Social Netw. Analys. Mining
Keywords
Field
DocType
Complex network,Community detection,Matrix factorization
Locality,Computer science,Matrix decomposition,Theoretical computer science,Non-negative matrix factorization,Complex network,Local area network
Journal
Volume
Issue
ISSN
8
1
1869-5450
Citations 
PageRank 
References 
1
0.37
19
Authors
4
Name
Order
Citations
PageRank
Hongyi Zhang122.75
Xingyu Niu210.37
Irwin King36751325.94
Michael R. Lyu410985529.03