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The Artificial Benchmark for Community Detection (ABCD) is a random graph model that incorporates community structure and follows a power-law distribution for both node degrees and community sizes. It produces graphs similar to the well-known LFR model but is faster, more interpretable, and analytically tractable. In this paper, we build on the core principles of ABCD to introduce a mABCD, a new variant designed for multilayer networks.

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The Multilayer Artificial Benchmark for Community Detection (mABCD)

  • 会议论文

  • 发表日期：

    2025年

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  • Piotr Bródka,
  • Michał Czuba,
  • Bogumił Kamiński,
  • Łukasz Kraiński,
  • Paweł Prałat,
  • François Théberge

摘要

The Artificial Benchmark for Community Detection (ABCD) is a random graph model that incorporates community structure and follows a power-law distribution for both node degrees and community sizes. It produces graphs similar to the well-known LFR model but is faster, more interpretable, and analytically tractable. In this paper, we build on the core principles of ABCD to introduce a mABCD, a new variant designed for multilayer networks.