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The Artificial Benchmark for Community Detection (ABCD) graph is a random graph model with community structure and power-law distribution for both degrees and community sizes. The model generates graphs similar to the well-known LFR model but is faster and more interpretable. In this paper, we use the underlying ingredients of the ABCD model, and its generalization to include outliers (ABCD+o), and introduce another variant for overlapping communities, \(\mathbf {ABCD{+}o}^2\) .

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The Artificial Benchmark for Community Detection with Outliers and Overlapping Communities ( \(\mathbf {ABCD{+}o}^2\) )

  • 会议论文

  • 发表日期：

    2025年

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  • Jordan Barrett,
  • Ryan DeWolfe,
  • Bogumił Kamiński,
  • Paweł Prałat,
  • Aaron Smith,
  • François Théberge

摘要

The Artificial Benchmark for Community Detection (ABCD) graph is a random graph model with community structure and power-law distribution for both degrees and community sizes. The model generates graphs similar to the well-known LFR model but is faster and more interpretable. In this paper, we use the underlying ingredients of the ABCD model, and its generalization to include outliers (ABCD+o), and introduce another variant for overlapping communities, \(\mathbf {ABCD{+}o}^2\) .