Role discovery for graph clustering

Bin Hui Chou, Einoshin Suzuki

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

2 被引用数 (Scopus)

抄録

Graph clustering is an important task of discovering the underlying structure in a network. Well-known methods such as the normalized cut and modularity-based methods are developed in the past decades. These methods may be called non-overlapping because they assume that a vertex belongs to one community. On the other hand, overlapping methods such as CPM, which assume that a vertex may belong to more than one community, have been drawing attention as the assumption fits the reality. We believe that existing overlapping methods are overly simple for a vertex located at the border of a community. That is, they lack careful consideration on the edges that link the vertex to its neighbors belonging to different communities. Thus, we propose a new graph clustering method, named RoClust, which uses three different kinds of roles, each of which represents a different kind of vertices that connect communities. Experimental results show that our method outperforms state-of-the-art methods of graph clustering.

本文言語英語
ホスト出版物のタイトルWeb Technologies and Applications - 13th Asia-Pacific Web Conference, APWeb 2011, Proceedings
ページ17-28
ページ数12
DOI
出版ステータス出版済み - 2011
イベント13th Asia-Pacific Conference on Web Technology, APWeb 2011 - Beijing, 中国
継続期間: 4月 18 20114月 20 2011

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6612 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

その他

その他13th Asia-Pacific Conference on Web Technology, APWeb 2011
国/地域中国
CityBeijing
Period4/18/114/20/11

!!!All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータサイエンス一般

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