关键词: 二分网络, 社区发现, 亲密度, 吸引力, 归一化互信息, 模块度

Abstract: Community division is a hot topic in the study of bipartite network, aiming at the existing bipartite network community detecting algorithm from different nodes with the problem of low accuracy, this paper proposes the bipartite network community detecting algorithm based on Intimacy and Attraction Algorithm（IAA）. The algorithm treats every U-type node as a community, through calculating the intimacy of each community and the attraction of the community merge communities, U-type node partition is obtained. At last, V-type nodes are divided into existing communities to obtain complete community division results. Through the analysis on artificial networks and real-world networks, normalized mutual information and modularity are used respectively as evaluation indicators. The experimental results show that IAA is able to mine the bipartite network community structure more effectively and has a better community division.

Key words: bipartite network, community detecting, intimacy, attraction, normalized mutual information, modularity