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20062024
most citedArtificial Benchmark for Community Detection with Outliers (ABCD+o)

19 citations · 43 across the 34 of their papers we have counts for

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16 papers · 1 filter

cs.SI2024

Modularity Based Community Detection in Hypergraphs

Bogumił Kamiński, Paweł Misiorek, Paweł Prałat +1

In this paper, we propose a scalable community detection algorithm using hypergraph modularity function, h-Louvain. It is an adaptation of the classical Louvain algorithm in the co…

cs.SI2023★ 1 cited

Self-similarity of Communities of the ABCD Model

Jordan Barrett, Bogumil Kaminski, Pawel Pralat +1

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…

cs.SI2023★ 1 cited

Predicting Properties of Nodes via Community-Aware Features

Bogumił Kamiński, Paweł Prałat, François Théberge +1

This paper shows how information about the network's community structure can be used to define node features with high predictive power for classification tasks. To do so, we defin…

cs.SI2023★ 19 cited

Artificial Benchmark for Community Detection with Outliers (ABCD+o)

Bogumił Kamiński, Paweł Prałat, François Théberge

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…

cs.SI2022★ 3 cited

Hypergraph Artificial Benchmark for Community Detection (h-ABCD)

Bogumił Kamiński, Paweł Prałat, François Théberge

The Artificial Benchmark for Community Detection (ABCD) graph is a recently introduced random graph model with community structure and power-law distribution for both degrees and c…

cs.SI2022★ 3 cited

Modularity of the ABCD Random Graph Model with Community Structure

Bogumil Kaminski, Bartosz Pankratz, Pawel Pralat +1

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…