A survey of community detection methods in multilayer networks
Community detection is one of the most popular researches in a variety of complex systems, ranging from biology to sociology. In recent years, there’s an increasing focus on the rapid development of more complicated networks, namely multilayer networks. Communities in a single-layer network are grou...
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| Published in | Data mining and knowledge discovery Vol. 35; no. 1; pp. 1 - 45 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.01.2021
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Community detection is one of the most popular researches in a variety of complex systems, ranging from biology to sociology. In recent years, there’s an increasing focus on the rapid development of more complicated networks, namely multilayer networks. Communities in a single-layer network are groups of nodes that are more strongly connected among themselves than the others, while in multilayer networks, a group of well-connected nodes are shared in multiple layers. Most traditional algorithms can rarely perform well on a multilayer network without modifications. Thus, in this paper, we offer overall comparisons of existing works and analyze several representative algorithms, providing a comprehensive understanding of community detection methods in multilayer networks. The comparison results indicate that the promoting of algorithm efficiency and the extending for general multilayer networks are also expected in the forthcoming studies. |
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| AbstractList | Community detection is one of the most popular researches in a variety of complex systems, ranging from biology to sociology. In recent years, there’s an increasing focus on the rapid development of more complicated networks, namely multilayer networks. Communities in a single-layer network are groups of nodes that are more strongly connected among themselves than the others, while in multilayer networks, a group of well-connected nodes are shared in multiple layers. Most traditional algorithms can rarely perform well on a multilayer network without modifications. Thus, in this paper, we offer overall comparisons of existing works and analyze several representative algorithms, providing a comprehensive understanding of community detection methods in multilayer networks. The comparison results indicate that the promoting of algorithm efficiency and the extending for general multilayer networks are also expected in the forthcoming studies. |
| Author | Wang, Dongqi Ren, Tao Chen, Dongming Huang, Xinyu |
| Author_xml | – sequence: 1 givenname: Xinyu surname: Huang fullname: Huang, Xinyu organization: Software College, Northeastern University – sequence: 2 givenname: Dongming orcidid: 0000-0001-7863-1230 surname: Chen fullname: Chen, Dongming email: chendm@mail.neu.edu.cn organization: Software College, Northeastern University – sequence: 3 givenname: Tao surname: Ren fullname: Ren, Tao organization: Software College, Northeastern University – sequence: 4 givenname: Dongqi surname: Wang fullname: Wang, Dongqi organization: Software College, Northeastern University |
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| Copyright | The Author(s) 2020 The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Keywords | Community detection Multiplex network Multilevel network Temporal network Multilayer network |
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| Title | A survey of community detection methods in multilayer networks |
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