Rough Net Approach for Community Detection Analysis in Complex Networks
| Autor: | Leticia Arco, Ivett Fuentes, Gonzalo Nápoles, Koen Vanhoof, Arian Pina |
|---|---|
| Přispěvatelé: | Rafael, Bello, Miao, Duoqian, Falcon, Rafael, Nakata, Michinori, Rosete, Alejandro, Ciucci, Davide, Informatics and Applied Informatics |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Multiplex Complex Networks
Computer science Community structure Vagueness Community Detection Anal- ysis Community detection analysis 02 engineering and technology Complex network Net (mathematics) computer.software_genre Article Visualization 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Extended Rough Set Theory Rough set Data mining Focus (optics) Representation (mathematics) computer Monoplex Complex Networks |
| Zdroj: | Rough Sets ISBN: 9783030527044 IJCRS Rough Sets Tilburg University-PURE |
| Popis: | Rough set theory has many interesting applications in circumstances which are characterized by vagueness. In this paper, the applications of rough set theory in community detection analysis is discussed based on the Rough Net definition. We will focus the application of Rough Net concept in community detection validity in both monoplex and multiplex complex networks. Also, the topological evolution estimation between adjacent layers in dynamic networks is discussed and a new visualization schema combining both complex network representation and Rough Net definition is adopted contributing to the understanding of the community structure. We provide some examples demonstrating how the Rough Net definition can be used to analyze the properties of the community structure in real-world networks, including dynamic networks. |
| Databáze: | OpenAIRE |
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