Community Detection in Multiplex Networks

被引：69

作者：

Magnani, Matteo ^{[1
]}

Hanteer, Obaida ^{[2
]}

Interdonato, Roberto ^{[3
,4
]}

Rossi, Luca ^{[2
]}

Tagarelli, Andrea ^{[5
]}

机构：

[1] Uppsala Univ, Infolab, Uppsala, Sweden

[2] IT Univ Copenhagen, Copenhagen, Denmark

[3] CIRAD, UMR TETIS, Montpellier, France

[4] Univ Montpellier, INRAE, CNRS, Cirad,TETIS,APT, Montpellier, France

[5] Univ Calabria, Arcavacata Di Rende, Italy

来源：

ACM COMPUTING SURVEYS | 2022年 / 54卷 / 03期

关键词：

Community detection; multiplex networks; multiplex community detection; MULTILAYER GRAPHS;

D O I：

10.1145/3444688

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A multiplex network models different modes of interaction among same-type entities. In this article, we provide a taxonomy of community detection algorithms in multiplex networks. We characterize the different algorithms based on various properties and we discuss the type of communities detected by each method. We then provide an extensive experimental evaluation of the reviewed methods to answer three main questions: to what extent the evaluated methods are able to detect ground-truth communities, to what extent different methods produce similar community structures, and to what extent the evaluated methods are scalable. One goal of this survey is to help scholars and practitioners to choose the right methods for the data and the task at hand, while also emphasizing when such choice is problematic.

引用

页数：35

共 63 条

[1]

Afsarmanesh Nazanin, 2018, P 2018 INT C SOC INF

[2]

[Anonymous], 2016, ABS161202377 CORR

[3] Modularity and community detection in bipartite networks [J].

Barber, Michael J. .

PHYSICAL REVIEW E, 2007, 76 (06)

[4] A framework for the construction of generative models for mesoscale structure in multilayer networks [J].

Bazzi, Marya ;

Jeub, Lucas G. S. ;

Arenas, Alex ;

Howison, Sam D. ;

Porter, Mason A. .

PHYSICAL REVIEW RESEARCH, 2020, 2 (02)

[5] ABACUS: frequent pAttern mining-BAsed Community discovery in mUltidimensional networkS [J].

Berlingerio, Michele ;

Pinelli, Fabio ;

Calabrese, Francesco .

DATA MINING AND KNOWLEDGE DISCOVERY, 2013, 27 (03) :294-320

[6] Finding and Characterizing Communities in Multidimensional Networks [J].

Berlingerio, Michele ;

Coscia, Michele ;

Giannotti, Fosca .

2011 INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2011), 2011, :490-494

[7]

Boden Brigitte., 2012, Proceedings of the 18th International Conference on Knowledge Discovery and Data Mining KDD, P1258, DOI [10.1145/2339530.2339726, DOI 10.1145/2339530.2339726]

[8] Clustering attributed graphs: Models, measures and methods [J].

Bothorel, Cecile ;

Cruz, Juan David ;

Magnani, Matteo ;

Micenkova, Barbora .

NETWORK SCIENCE, 2015, 3 (03) :408-444

[9] Mining Community Structures in Multidimensional Networks [J].

Boutemine, Oualid ;

Bouguessa, Mohamed .

ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA, 2017, 11 (04)

[10]

Brodka P., 2011, 2011 International Conference on Computational Aspects of Social Networks (CASoN 2011), P237, DOI 10.1109/CASON.2011.6085951

← 1 2 3 4 5 6 7 →