Modularity based community detection in hypergraphs
[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee
2024
scientific article
english
- hypergraph
- communities
- clusters
- modularity
EN 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 context of hypergraphs. We observe that a direct application of the Louvain algorithm to optimize the hypergraph modularity function often fails to find meaningful communities. We propose a solution to this issue by adjusting the initial stage of the algorithm via carefully and dynamically tuned linear combination of the graph modularity function of the corresponding two-section graph and the desired hypergraph modularity function. The process is guided by Bayesian optimization of the hyper-parameters of the proposed procedure. Various experiments on synthetic as well as real-world networks are performed showing that this process yields improved results in various regimes.
21.10.2024
cnae041-1 - cnae041-26
Article Number: cnae041
CC BY (attribution alone)
czasopismo hybrydowe
final published version
at the time of publication
100
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