RT Conference Proceedings
T1 Fuzzy Sugeno λ-measures and theirs applications to community detection problems
A1 Gutiérrez García-Pardo, Inmaculada
A1 Castro Cantalejo, Javier
A1 Gómez González, Daniel
A1 Espínola Vílchez, María Rosario
AB In this paper we propose a new framework for community detection problems. The starting point is a n-vector which defines some evidence about the elements of a finite set. This vector is used to build an interaction measure between the n elements of the set to which it refers. This interaction measure is represented by a Sugeno λ-measure to which we make it being also a fuzzy measure. Then, we obtain the weighted graph associated with this new capacity measure. To carry on with it, we make use of the Shapley value. We also introduce the notion of extended vector fuzzy graph, which relates a graph with the capacity measure introduced in this work. Finally, we use a community detection method, based on Louvain algorithm, to search a cluster structure in the weighted graph. This partition is based on the relations among the individuals obtained from the initial vector. Let us note that in the case that there exist some connections among the elements, apart from their affinity, we can combine this extra information with that given by the vector, in order to obtain groups with highly-knit elements among which there are strong relations.
SN 978-1-7281-6932-3
SN 1544-5615
YR 2020
FD 2020
LK https://hdl.handle.net/20.500.14352/130726
UL https://hdl.handle.net/20.500.14352/130726
LA eng
NO I. Gutiérrez, D. Gómez, J. Castro and R. Espínola, "Fuzzy Sugeno λ-measures and theirs applications to community detection problems," 2020 IEEE International conference on fuzzy systems (FUZZ-IEEE), Glasgow, UK, 2020, pp. 1-8, doi: 10.1109/FUZZ48607.2020.9177794
DS Docta Complutense
RD 27 mar 2026