Finding a dense subgraph with sparse cut

Atsushi Miyauchi, Naonori Kakimura

研究成果: Conference contribution

3 引用 (Scopus)

抜粋

Community detection is one of the fundamental tasks in graph mining, which has many real-world applications in diverse domains. In this study, we propose an optimization model for finding a community that is densely connected internally but sparsely connected to the rest of the graph. The model extends the densest subgraph problem, in which we maximize the density while minimizing the average cut size. We first show that our proposed model can be solved efficiently. Then we design two polynomial-time exact algorithms based on linear programming and a maximum flow algorithm, respectively. Moreover, to deal with larger-sized graphs in practice, we present a scalable greedy algorithm that runs in almost linear time with theoretical performance guarantee of the output. In addition, as our model is closely related to a quality function called the modularity density, we show that our algorithms can also be used to find global community structure in a graph. With thorough experiments using well-known real-world graphs, we demonstrate that our algorithms are highly effective in finding a suitable community in a graph. For example, for web-Google, our algorithm finds a solution with more than 99.1% density and less than 3.1% cut size, compared with a solution obtained by a baseline algorithm for the densest subgraph problem.

元の言語English
ホスト出版物のタイトルCIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management
編集者Norman Paton, Selcuk Candan, Haixun Wang, James Allan, Rakesh Agrawal, Alexandros Labrinidis, Alfredo Cuzzocrea, Mohammed Zaki, Divesh Srivastava, Andrei Broder, Assaf Schuster
出版者Association for Computing Machinery
ページ547-556
ページ数10
ISBN(電子版)9781450360142
DOI
出版物ステータスPublished - 2018 10 17
イベント27th ACM International Conference on Information and Knowledge Management, CIKM 2018 - Torino, Italy
継続期間: 2018 10 222018 10 26

Other

Other27th ACM International Conference on Information and Knowledge Management, CIKM 2018
Italy
Torino
期間18/10/2218/10/26

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

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  • これを引用

    Miyauchi, A., & Kakimura, N. (2018). Finding a dense subgraph with sparse cut. : N. Paton, S. Candan, H. Wang, J. Allan, R. Agrawal, A. Labrinidis, A. Cuzzocrea, M. Zaki, D. Srivastava, A. Broder, & A. Schuster (版), CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management (pp. 547-556). Association for Computing Machinery. https://doi.org/10.1145/3269206.3271720