Multiple bipolar fuzzy measures: an application to community detection problems for networks with additional information
arXiv:2402.04786 · doi:10.2991/ijcis.d.201012.001 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.
14 pages
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