Presentation information

General Session

General Session » [GS] J-3 Data mining

[4B2-J-3] Data mining: structures and clusters

Fri. Jun 7, 2019 12:00 PM - 1:20 PM Room B (2F Main hall B)

Chair:Shigeru Maya Reviewer:Kohei Miyaguchi

12:20 PM - 12:40 PM

[4B2-J-3-02] Community detection in bipartite networks by multi label propagation algorithm

〇Hibiki Taguchi1, Tsuyoshi Murata1 (1. Tokyo Institute of Technology)

Keywords:community detection, bipartite networks, multi label propagation

Community detection is an important topic in complex networks.
A bipartite network is a special type of network, whose nodes can be divided into two disjoint sets and each edge connects between different types of nodes. In bipartite networks, there are two types of community definition, one-to-one correspondence and many-to-many correspondence between communities. The latter is better to represent realistic community structure in bipartite networks. However, few method can extract this type of structure.
In this paper, we propose BiMLPA, based on multi label propagation algorithm, to detect many-to-many correspondence between communities in bipartite networks. Experimental results on real-world networks show that BiMLPA is effective and stable for detecting communities.