Detection of Maximal Balance Clique Using Three-way Concept Lattice

Detection of Maximal Balance Clique Using Three-way Concept Lattice
  • Yixuan Yang
  • 박두순
  • Fei Hao
  • Sony Peng
  • 이혜정
  • 외 1명
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초록

In the era marked by information inundation, social network analysis is the most important part of big dataanalysis, with clique detection being a key technology in social network mining. Also, detecting maximalbalance clique in signed networks with positive and negative relationships is essential. In this paper, we presenttwo algorithms. The first one is an algorithm, MCDA1, that detects the maximal balance clique using theimproved three-way concept lattice algorithm and object-induced three-way concept lattice (OE-concept). Thesecond one is an improved formal concept analysis algorithm, MCDA2, that improves the efficiency ofmemory. Additionally, we tested the execution time of our proposed method with four real-world datasets.

키워드

Formal Concept AnalysisMaximal Balanced CliqueSigned NetworksThree-Way Concept
제목
Detection of Maximal Balance Clique Using Three-way Concept Lattice
제목 (타언어)
Detection of Maximal Balance Clique Using Three-way Concept Lattice
저자
Yixuan Yang박두순Fei HaoSony Peng이혜정홍민표
DOI
10.3745/JIPS.01.0094
발행일
2023-04
유형
Article
저널명
JIPS(Journal of Information Processing Systems)
19
2
페이지
189 ~ 202