Rough Net Approach for Community Detection Analysis in Complex Networks

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

doi:10.1007/978-3-030-52705-1_30

Rough Net Approach for Community Detection Analysis in Complex Networks

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

Informatics and Applied Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research

1 Citation (Scopus)

Abstract

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 language	English
Title of host publication	Rough Sets
Subtitle of host publication	Proceedings of the International Joint Conference (IJCRS 2020), Havana, Cuba, June 29 – July 3, 2020
Editors	Rafael Bello, Duoqian Miao, Rafael Falcón, Michinori Nakata, Alejandro Rosete, Davide Ciucci
Publisher	Springer Verlag
Pages	401–415
Number of pages	15
Volume	12179
ISBN (Electronic)	978-3-030-52705-1
ISBN (Print)	978-3-030-52704-4
DOIs	https://doi.org/10.1007/978-3-030-52705-1_30
Publication status	Published - 7 Jul 2020
Event	International Joint Conference on Rough Sets - Melia Habana Hotel, Havana, Cuba Duration: 29 Jun 2020 → 3 Jul 2020 https://easychair.org/cfp/IJCRS2020

Publication series

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer
Volume	12179
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Joint Conference on Rough Sets
Abbreviated title	IJCRS 2020
Country/Territory	Cuba
City	Havana
Period	29/06/20 → 3/07/20
Internet address	https://easychair.org/cfp/IJCRS2020

Access to Document

10.1007/978-3-030-52705-1_30

https://link.springer.com/chapter/10.1007/978-3-030-52705-1_30

Cite this

Fuentes Herrera, I. E., Pina, A., Nápoles, G., Arco, L., & Vanhoof, K. (2020). Rough Net Approach for Community Detection Analysis in Complex Networks. In R. Bello, D. Miao, R. Falcón, M. Nakata, A. Rosete, & D. Ciucci (Eds.), Rough Sets: Proceedings of the International Joint Conference (IJCRS 2020), Havana, Cuba, June 29 – July 3, 2020 (Vol. 12179, pp. 401–415). (Lecture Notes in Artificial Intelligence; Vol. 12179). Springer Verlag. https://doi.org/10.1007/978-3-030-52705-1_30

Fuentes Herrera, Ivett Elena ; Pina, Arian ; Nápoles, Gonzalo ; Arco, Leticia ; Vanhoof, Koen. / Rough Net Approach for Community Detection Analysis in Complex Networks. Rough Sets: Proceedings of the International Joint Conference (IJCRS 2020), Havana, Cuba, June 29 – July 3, 2020. editor / Rafael Bello ; Duoqian Miao ; Rafael Falcón ; Michinori Nakata ; Alejandro Rosete ; Davide Ciucci. Vol. 12179 Springer Verlag, 2020. pp. 401–415 (Lecture Notes in Artificial Intelligence).

@inproceedings{791708831d9041788b5ba0e10130c217,

title = "Rough Net Approach for Community Detection Analysis in Complex Networks",

abstract = "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.",

author = "{Fuentes Herrera}, {Ivett Elena} and Arian Pina and Gonzalo N{\'a}poles and Leticia Arco and Koen Vanhoof",

year = "2020",

month = jul,

day = "7",

doi = "10.1007/978-3-030-52705-1_30",

language = "English",

isbn = "978-3-030-52704-4",

volume = "12179",

series = "Lecture Notes in Artificial Intelligence",

publisher = "Springer Verlag",

pages = "401–415",

editor = "Rafael Bello and Duoqian Miao and Rafael Falc{\'o}n and Michinori Nakata and Alejandro Rosete and Davide Ciucci",

booktitle = "Rough Sets",

address = "Germany",

note = "International Joint Conference on Rough Sets, IJCRS 2020 ; Conference date: 29-06-2020 Through 03-07-2020",

url = "https://easychair.org/cfp/IJCRS2020",

}

Fuentes Herrera, IE, Pina, A, Nápoles, G, Arco, L & Vanhoof, K 2020, Rough Net Approach for Community Detection Analysis in Complex Networks. in R Bello, D Miao, R Falcón, M Nakata, A Rosete & D Ciucci (eds), Rough Sets: Proceedings of the International Joint Conference (IJCRS 2020), Havana, Cuba, June 29 – July 3, 2020. vol. 12179, Lecture Notes in Artificial Intelligence, vol. 12179, Springer Verlag, pp. 401–415, International Joint Conference on Rough Sets, Havana, Cuba, 29/06/20. https://doi.org/10.1007/978-3-030-52705-1_30

Rough Net Approach for Community Detection Analysis in Complex Networks. / Fuentes Herrera, Ivett Elena; Pina, Arian; Nápoles, Gonzalo; Arco, Leticia; Vanhoof, Koen.

Rough Sets: Proceedings of the International Joint Conference (IJCRS 2020), Havana, Cuba, June 29 – July 3, 2020. ed. / Rafael Bello; Duoqian Miao; Rafael Falcón; Michinori Nakata; Alejandro Rosete; Davide Ciucci. Vol. 12179 Springer Verlag, 2020. p. 401–415 (Lecture Notes in Artificial Intelligence; Vol. 12179).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research

TY - GEN

T1 - Rough Net Approach for Community Detection Analysis in Complex Networks

AU - Fuentes Herrera, Ivett Elena

AU - Pina, Arian

AU - Nápoles, Gonzalo

AU - Arco, Leticia

AU - Vanhoof, Koen

PY - 2020/7/7

Y1 - 2020/7/7

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85088589520&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-52705-1_30

DO - 10.1007/978-3-030-52705-1_30

M3 - Conference paper

SN - 978-3-030-52704-4

VL - 12179

T3 - Lecture Notes in Artificial Intelligence

SP - 401

EP - 415

BT - Rough Sets

A2 - Bello, Rafael

A2 - Miao, Duoqian

A2 - Falcón, Rafael

A2 - Nakata, Michinori

A2 - Rosete, Alejandro

A2 - Ciucci, Davide

PB - Springer Verlag

T2 - International Joint Conference on Rough Sets

Y2 - 29 June 2020 through 3 July 2020

ER -

Fuentes Herrera IE, Pina A, Nápoles G, Arco L, Vanhoof K. Rough Net Approach for Community Detection Analysis in Complex Networks. In Bello R, Miao D, Falcón R, Nakata M, Rosete A, Ciucci D, editors, Rough Sets: Proceedings of the International Joint Conference (IJCRS 2020), Havana, Cuba, June 29 – July 3, 2020. Vol. 12179. Springer Verlag. 2020. p. 401–415. (Lecture Notes in Artificial Intelligence). https://doi.org/10.1007/978-3-030-52705-1_30

Rough Net Approach for Community Detection Analysis in Complex Networks

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this