Detection of Maximal Balance Clique Using Three-way Concept Lattice

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.