Acknowledgement
This research was supported by the National Research Foundation of Korea (No. NRF-2022R1A2C1005921) and BK21 FOUR (Fostering Outstanding Universities for Research) (No.5199990914048)
Proceedings of the Korea Information Processing Society Conference (한국정보처리학회:학술대회논문집)
- 2022.11a
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- Pages.374-376
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- 2022
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- 2005-0011(pISSN)
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- 2671-7298(eISSN)
DOI QR Code
A Novel Study on Community Detection Algorithm Based on Cliques Mining
클리크 마이닝에 기반한 새로운 커뮤니티 탐지 알고리즘 연구
- Yang, Yixuan (Dept. of Software Convergence, Soonchunhyang University) ;
- Peng, Sony (Dept. of Software Convergence, Soonchunhyang University) ;
- Park, Doo-Soon (Dept. of Software Convergence, Soonchunhyang University) ;
- Kim, Seok-Hoon (Dept. of Software Convergence, Soonchunhyang University) ;
- Lee, HyeJung (Institute for Artificial Intelligence and Software, Soonchunhyang University) ;
- Siet, Sophort (Dept. of Software Convergence, Soonchunhyang University)
- 양예선 (순천향대학교 소프트웨어융합학과) ;
- 펭소니 (순천향대학교 소프트웨어융합학과) ;
- 박두순 (순천향대학교 소프트웨어융합학과) ;
- 김석훈 (순천향대학교 소프트웨어융합학과) ;
- 이혜정 (순천향대학교 AI.SW 교육원) ;
- 싯소포호트 (순천향대학교 소프트웨어융합학과)
- Published : 2022.11.21
Abstract
Community detection is meaningful research in social network analysis, and many existing studies use graph theory analysis methods to detect communities. This paper proposes a method to detect community by detecting maximal cliques and obtain the high influence cliques by high influence nodes, then merge the cliques with high similarity in social network.
Keywords