RT Journal Article
T1 Group definition based on flow in community detection
A1 Barroso, María
A1 Gutiérrez García-Pardo, Inmaculada
A1 Gómez González, Daniel
A1 Castro Cantalejo, Javier
A1 Espínola, Rosa
AB Community detection problems are one of the hottest disciplines in social network analysis. Nevertheless, most of the related algorithms are specific for non-directed networks, or are based on a density concept of group. In this paper, we deal with a new concept of community for directed networks that is based on the classical flow concept. A community is strong and cohesive if their members can communicate among them. With the aim of dealing with the identification of this new class of groups, in this work, we propose the use of fuzzy measures to represent the flow capacity of a group. We also provide a competitive community detection algorithm that focus on the identification of these new class of flow-based community
PB PubMed Central
YR 2020
FD 2020
LK https://hdl.handle.net/20.500.14352/129914
UL https://hdl.handle.net/20.500.14352/129914
LA eng
NO Barroso M, Gutiérrez I, Gómez D, Castro J, Espínola R. Group Definition Based on Flow in Community Detection. Information Processing and Management of Uncertainty in Knowledge-Based Systems. 2020 May 16;1239:524–38. doi: 10.1007/978-3-030-50153-2_39. PMCID: PMC7274715.
DS Docta Complutense
RD 22 mar 2026