Multiple bipolar fuzzy measures: an application to community detection problems for networks with additional information
Loading...
Full text at PDC
Publication date
2020
Advisors (or tutors)
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Atlantis Press, Springer
Citation
Gutiérrez, I., Gómez, D., Castro, J. et al. Multiple Bipolar Fuzzy Measures: An Application to Community Detection Problems for Networks with Additional Information. Int J Comput Intell Syst 13, 1636–1649 (2020). https://doi.org/10.2991/ijcis.d.201012.001
Abstract
In this paper we introduce the concept of multiple bipolar fuzzy measures as a generalization of a bipolar fuzzy measure. We also propose a new definition of a group, which is based on the multidimensional bipolar fuzzy relations of its elements. Taking into account this information, we provide a novel procedure (based on the well-known Louvain algorithm) to deal with community detection problems. This new method considers the multidimensional bipolar information provided by multiple bipolar fuzzy measures, as well as the information provided by a graph. We also give some detailed computational tests, obtained from the application of this algorithm in several benchmark models.