Rough Net Approach for Community Detection Analysis in Complex Networks

Ivett Elena Fuentes Herrera, Arian Pina, Gonzalo Nápoles, Leticia Arco, Koen Vanhoof

Research output: Chapter in Book/Report/Conference proceedingConference paperResearch

1 Citation (Scopus)


Rough set theory has many interesting applications in circumstances characterized by vagueness. In this paper, the applications of rough set theory in community detection analysis are discussed based on the Rough Net definition. We will focus the application of Rough Net on community detection validity in both monoplex and multiplex networks. Also, the topological evolution estimation between adjacent layers in dynamic networks is discussed and a new community interaction visualization approach combining both complex network representation and Rough Net definition is adopted to interpret the community structure. We provide some examples that illustrate how the Rough Net definition can be used to analyze the properties of the community structure in real-world networks, including dynamic networks.
Original languageEnglish
Title of host publicationRough Sets
Subtitle of host publicationProceedings of the International Joint Conference (IJCRS 2020), Havana, Cuba, June 29 – July 3, 2020
EditorsRafael Bello, Duoqian Miao, Rafael Falcón, Michinori Nakata, Alejandro Rosete, Davide Ciucci
PublisherSpringer Verlag
Number of pages15
ISBN (Electronic)978-3-030-52705-1
ISBN (Print)978-3-030-52704-4
Publication statusPublished - 7 Jul 2020
EventInternational Joint Conference on Rough Sets - Melia Habana Hotel, Havana, Cuba
Duration: 29 Jun 20203 Jul 2020

Publication series

NameLecture Notes in Artificial Intelligence
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Joint Conference on Rough Sets
Abbreviated titleIJCRS 2020
Internet address


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