4 papers
Twinning Complex Networked Systems: Data-Driven Calibration of the mABCD Synthetic Graph Generator
Piotr Bródka, MichaÅ Czuba, BogumiÅ KamiÅski +4
The increasing availability of relational data has contributed to a growing reliance on network-based representations of complex systems. Over time, these models have evolved to ca…
The Artificial Benchmark for Community Detection with Outliers and Overlapping Communities (ABCD+)
Jordan Barrett, Ryan DeWolfe, BogumiÅ KamiÅski +3
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…
Multilayer Artificial Benchmark for Community Detection (mABCD)
Åukasz KraiÅski, MichaÅ Czuba, Piotr Bródka +3
One of the most persistent challenges in network science is the development of various synthetic graph models to support subsequent analyses. Among the most notable frameworks addr…
Improving community detection via community association strength scores
Jordan Barrett, Ryan DeWolfe, BogumiÅ KamiÅski +3
Community detection methods play a central role in understanding complex networks by revealing highly connected subsets of entities. However, most community detection algorithms ge…