CR-Graph: Community Reinforcement for Accurate Community Detection

Yoonsuk Kang, Jun Seok Lee, Won Yong Shin, Sang Wook Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present CR-Graph (community reinforcement on graphs), a novel method that helps existing algorithms to perform more-accurate community detection (CD). Toward this end, CR-Graph strengthens the community structure of a given original graph by adding non-existent predicted intra-community edges and deleting existing predicted inter-community edges. To design CR-Graph, we propose the following two strategies: (1) predicting intra-community and inter-community edges (i.e., the type of edges) and (2) determining the amount of edges to be added/deleted. To show the effectiveness of CR-Graph, we conduct extensive experiments with various CD algorithms on 7 synthetic and 4 real-world graphs. The results demonstrate that CR-Graph improves the accuracy of all underlying CD algorithms universally and consistently.

Original languageEnglish
Title of host publicationCIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages2077-2080
Number of pages4
ISBN (Electronic)9781450368599
DOIs
Publication statusPublished - 2020 Oct 19
Event29th ACM International Conference on Information and Knowledge Management, CIKM 2020 - Virtual, Online, Ireland
Duration: 2020 Oct 192020 Oct 23

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference29th ACM International Conference on Information and Knowledge Management, CIKM 2020
Country/TerritoryIreland
CityVirtual, Online
Period20/10/1920/10/23

Bibliographical note

Funding Information:
This research was supported by (1) the National Research Foundation of Korea grant funded by the Korea government (NRF-2020R1A2B5B03001960), (2) the National Research Foundation of Korea grant funded by the Korea government (2018R1A5A7059549), and (3) the Next-Generation Information Computing Development Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT (NRF-2017M3C4A7069440).

Publisher Copyright:
© 2020 ACM.

All Science Journal Classification (ASJC) codes

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

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