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Detecting one-mode communities in bipartite networks by bipartite clustering triangular.
- Source :
-
Physica A . Sep2016, Vol. 457, p307-315. 9p. - Publication Year :
- 2016
-
Abstract
- In this paper, an algorithm is proposed to detect one-mode community structures in bipartite networks, and to deduce which one-mode community structures are weighted. After analyzing the topological properties in bipartite networks, bipartite clustering triangular is introduced. First, bipartite networks are projected into two weighted one-mode networks by bipartite clustering triangular. Then all the maximal sub-graphs from two one-mode weighted networks are extracted and the maximal sub-graphs are merged together using a weighted clustering threshold. In addition, the proposed algorithm successfully finds overlapping vertices between one-mode communities. Experimental results using some real-world network data shows that the performance of the proposed algorithm is satisfactory. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03784371
- Volume :
- 457
- Database :
- Academic Search Index
- Journal :
- Physica A
- Publication Type :
- Academic Journal
- Accession number :
- 115213794
- Full Text :
- https://doi.org/10.1016/j.physa.2016.03.002