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- W4377291738 abstract "The Artificial Benchmark for Community Detection graph (ABCD) is a random graph model with community structure and power-law distribution for both degrees and community sizes. The model generates graphs with similar properties as the well-known LFR one, and its main parameter $xi$ can be tuned to mimic its counterpart in the LFR model, the mixing parameter $mu$. In this paper, we extend the ABCD model to include potential outliers. We perform some exploratory experiments on both the new ABCD+o model as well as a real-world network to show that outliers possess some desired, distinguishable properties." @default.
- W4377291738 created "2023-05-23" @default.
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- W4377291738 date "2023-05-22" @default.
- W4377291738 modified "2023-09-30" @default.
- W4377291738 title "Artificial benchmark for community detection with outliers (ABCD+o)" @default.
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- W4377291738 doi "https://doi.org/10.1007/s41109-023-00552-9" @default.
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