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Semi-Supervised Community Detection via Constraint Matrix Construction and Active Node Selection

Zhang, Suqi, Wu, Junyan, Li, Jianxin, Gu, Junhua, Tang, Xianchao and Xu, Xinyun 2020, Semi-Supervised Community Detection via Constraint Matrix Construction and Active Node Selection, IEEE Access, vol. 8, pp. 39078-39090, doi: 10.1109/access.2019.2962634.

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Title Semi-Supervised Community Detection via Constraint Matrix Construction and Active Node Selection
Author(s) Zhang, Suqi
Wu, Junyan
Li, JianxinORCID iD for Li, Jianxin orcid.org/0000-0002-9059-330X
Gu, Junhua
Tang, Xianchao
Xu, Xinyun
Journal name IEEE Access
Volume number 8
Start page 39078
End page 39090
Total pages 13
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Place of publication Piscataway, N.J.
Publication date 2020
ISSN 2169-3536
2169-3536
Keyword(s) community detection
non-negative matrix factorization
semi-supervised learning
active learning
Summary Identification of community structures is essential for characterizing and analyzing complex networks. Having focusing primarily on network topological structures, most existing methods for community detection ignore two types of non-topological relationships among nodes, i.e., pairwise “must-link” constraints among pairs of nodes and labels of nodes, such as functions they may have. Here, we present a novel semi-supervised and active learning method for community detection to integrate these two types of information of a network so as to increase the accuracy of community identification. Our new method will honor the “must-link” relationship without introducing new parameters and is efficient with a guaranteed convergence. An essential component of the method is a linear representation that is particularly suited to an active learning to help select the most critical nodes that impact community discovery. We present results from extensive experiments on synthetic and real networks to show the superior performance of the new methods over the existing approaches.
Language eng
DOI 10.1109/access.2019.2962634
Indigenous content off
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30135702

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.