Graph models help understand network dynamics and evolution. Creating graphs with controlled topology and embedded partitions is a common strategy for evaluating community detection algorithms. However, existing benchmarks often overlook the need to …
Community detection is a crucial task in many graph data analysis pipelines, with applications ranging from social networks to biology and transportation systems. This work introduces FO-SM-CD, a novel constraint programming framework for community …
Discovering community structure in complex networks is a mature field since a tremendous number of community detection methods have been introduced in the literature. Nevertheless, it is still very challenging for practitioners to choose in each …