Tahalea, Sylvert Prian, Krész, Miklós (2025) Betweenness-driven overlapping label propagation community detection Annales Mathematicae et Informaticae. 61. pp. 229-247. ISSN 1787-6117 (Online)
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Absztrakt (kivonat)
Community detection holds significant value in discovering hidden structures in complex networks. In this paper, we propose a betweennessdriven community detection based on the label propagation algorithm. First, at the multiple labels’ assignment phase, we detect communities using label propagation and apply labels for the nodes using the betweenness and degree centrality as references. Second, we refine the modularity and stability using several configurations, such as global modularity and stability pruning, to avoid nodes that have not changed for several iterations. This algorithm was tested with the most common datasets, such as Zachary’s Karate Club Network, Polbooks, Football, and 12 LFR synthetic datasets, which resulted in improved scores on modularity, overlapping normalised mutual information, omega index, generalized F1-score, and extended various pieces of information.
| Mű típusa: | Folyóiratcikk - Journal article |
|---|---|
| Szerző: | Szerző neve Email MTMT azonosító ORCID azonosító Közreműködés Tahalea, Sylvert Prian NEM RÉSZLETEZETT NEM RÉSZLETEZETT NEM RÉSZLETEZETT Szerző Krész, Miklós NEM RÉSZLETEZETT NEM RÉSZLETEZETT NEM RÉSZLETEZETT Szerző |
| Megjegyzés: | The research was supported by the BioLOG project: the second author is grateful for the support of the National Centre of Science (NCN) through grant DEC-2020/39/I/HS4/03533, the Slovenian Research and Innovation Agency (ARIS) through grant N1-0223 and the Austrian Science Fund (FWF) through grant I 5443-N. This work is supported by the ARIS research program P1-0404 and by the research program CogniCom (0013103) at the University of Primorska. |
| Kapcsolódó URL-ek: | |
| Kulcsszavak: | network, graph, overlapping, community detection, label propagation algorithm |
| Folyóirat alcíme: | Selected papers of the International Conference on Formal Methods and Foundations of Artificial Intelligence |
| Nyelv: | angol |
| Kötetszám: | 61. |
| DOI azonosító: | 10.33039/ami.2025.10.012 |
| ISSN: | 1787-6117 (Online) |
| Felhasználó: | Tibor Gál |
| Dátum: | 29 Okt 2025 12:58 |
| Utolsó módosítás: | 29 Okt 2025 12:58 |
| URI: | http://publikacio.uni-eszterhazy.hu/id/eprint/8838 |
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