Multiple bipolar fuzzy measures: an application to community detection problems for networks with additional information
<|reference_start|>Multiple bipolar fuzzy measures: an application to community detection problems for networks with additional information: 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.<|reference_end|>
@article{gutiérrez2024multiple,
    title={Multiple bipolar fuzzy measures: an application to community detection
  problems for networks with additional information},
    author={Inmaculada Guti'errez, Daniel G'omez, Javier Castro and Rosa
  Esp'inola},
    journal={International Journal of Computational Intelligence Systems, 2020,
  13(1), pp. 1636-1649},
    year={2024},
    doi={10.2991/ijcis.d.201012.001 10.2991/ijcis.d.201012.001},
    archivePrefix={arXiv},
    eprint={2402.04786},
    primaryClass={cs.SI math.ST physics.soc-ph stat.TH}
}