Fuzzy Community detection based on grouping and overlapping functions
One of the main challenges of fuzzy community detection problems is to be able to measure the quality of a fuzzy partition. In this paper, we present an alternative way of measure the quality of a fuzzy community detection output based on n-dimensional grouping and overlapping functions that general...
| Autores: | , , , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/35772 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/35772 |
| Access Level: | acceso abierto |
| Palabra clave: | 519.2 Overlaps functions Grouping functions Community detection Estadística matemática (Matemáticas) 1209 Estadística |
| Sumario: | One of the main challenges of fuzzy community detection problems is to be able to measure the quality of a fuzzy partition. In this paper, we present an alternative way of measure the quality of a fuzzy community detection output based on n-dimensional grouping and overlapping functions that generalize the classical modularity for crisp community detection problems and also for crisp overlapping community detection problems. |
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