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This paper introduces an innovative method for identifying fuzzy and overlapping communities in graphs using Formal Concept Analysis (FCA). While several initial works have explored the application of FCA to non-overlapping community detection, this paper aims to extend one of these approaches to the detection of overlapping communities. We conduct experiments on various benchmark graphs, including both synthetic and real networks. The performance of the proposed method is evaluated using well-known metrics and compared with other algorithms in the literature.

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Fuzzy and Overlapping Communities Detection: An Improved Approach Using Formal Concept Analysis

  • 会议论文

  • 发表日期：

    2025年

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  • Martin Waffo Kemgne,
  • Christophe Demko,
  • Karell Bertet,
  • Jean-Loup Guillaume

摘要

This paper introduces an innovative method for identifying fuzzy and overlapping communities in graphs using Formal Concept Analysis (FCA). While several initial works have explored the application of FCA to non-overlapping community detection, this paper aims to extend one of these approaches to the detection of overlapping communities. We conduct experiments on various benchmark graphs, including both synthetic and real networks. The performance of the proposed method is evaluated using well-known metrics and compared with other algorithms in the literature.