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Detection of Maximal Balance Clique Using Three-way Concept LatticeDetection of Maximal Balance Clique Using Three-way Concept Lattice

Other Titles
Detection of Maximal Balance Clique Using Three-way Concept Lattice
Authors
Yixuan Yang박두순Fei HaoSony Peng이혜정홍민표
Issue Date
Apr-2023
Publisher
한국정보처리학회
Keywords
Formal Concept Analysis; Maximal Balanced Clique; Signed Networks; Three-Way Concept
Citation
JIPS(Journal of Information Processing Systems), v.19, no.2, pp 189 - 202
Pages
14
Journal Title
JIPS(Journal of Information Processing Systems)
Volume
19
Number
2
Start Page
189
End Page
202
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/22506
DOI
10.3745/JIPS.01.0094
ISSN
1976-913X
2092-805X
Abstract
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.
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