RT Journal Article
T1 Improving community detection algorithms in directed graphs with fuzzy measures. An application to mobility networks
A1 Gutiérrez García-Pardo, Inmaculada
A1 Barroso Pérez, María
A1 Gómez González, Daniel
A1 Castro Cantalejo, Javier
AB This paper proposes a novel methodology to enhance any community detection algorithm for directed networks by introducing a flow-based fuzzy measure, which improves both partition quality and the interpretability of the algorithm. To do so, we focus on a novel aggregation paradigm which combines social networks with fuzzy measures. We explore the potential of incorporating information from fuzzy measures, specifically with a flow capacity measure, to improve and optimize community detection algorithms. We present a detailed evaluation process to demonstrate the effectiveness of this methodology. To achieve this, we analyze a robust repository of databases, using several classical community detection techniques. A comprehensive comparison of classic results with the new methodology demonstrates the effectiveness of the presented aggregation paradigm. We reach a more conclusive understanding of the impact of our methodology through the application of machine learning techniques. Therefore, the proposed methodology enhances community detection performance in directed networks by incorporating flow-based fuzzy measures. We also illustrate its effectiveness through a case study. It showcases improved partition quality compared to traditional algorithms, along with theoretical insights into the fuzzy approach.
PB Elsevier
SN 0957-4174
YR 2025
FD 2025-01-08
LK https://hdl.handle.net/20.500.14352/113971
UL https://hdl.handle.net/20.500.14352/113971
LA eng
NO García-Pardo, I.G. et al. (2025) “Improving community detection algorithms in directed graphs with fuzzy measures. An application to mobility networks,” Expert Systems with Applications, 269, p. 126305. Available at: https://doi.org/10.1016/j.eswa.2024.126305
NO Gobierno de España, Gran Plan Nacional de I+D+i
DS Docta Complutense
RD 12 abr 2025