A Graph-Cut-Based Approach to Community Detection in Networks
Networks can be used to model various aspects of our lives as well as relations among many real-world entities and objects. To detect a community structure in a network can enhance our understanding of the characteristics, properties, and inner workings of the network. Therefore, there has been sign...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/12/6218 |
| _version_ | 1827662536765341696 |
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| author | Hyungsik Shin Jeryang Park Dongwoo Kang |
| author_facet | Hyungsik Shin Jeryang Park Dongwoo Kang |
| author_sort | Hyungsik Shin |
| collection | DOAJ |
| description | Networks can be used to model various aspects of our lives as well as relations among many real-world entities and objects. To detect a community structure in a network can enhance our understanding of the characteristics, properties, and inner workings of the network. Therefore, there has been significant research on detecting and evaluating community structures in networks. Many fields, including social sciences, biology, engineering, computer science, and applied mathematics, have developed various methods for analyzing and detecting community structures in networks. In this paper, a new community detection algorithm, which repeats the process of dividing a community into two smaller communities by finding a minimum cut, is proposed. The proposed algorithm is applied to some example network data and shows fairly good community detection results with comparable modularity <i>Q</i> values. |
| first_indexed | 2024-03-10T00:28:23Z |
| format | Article |
| id | doaj.art-281e6d8a6dd64add8a47341b152e0bc9 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T00:28:23Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-281e6d8a6dd64add8a47341b152e0bc92023-11-23T15:29:48ZengMDPI AGApplied Sciences2076-34172022-06-011212621810.3390/app12126218A Graph-Cut-Based Approach to Community Detection in NetworksHyungsik Shin0Jeryang Park1Dongwoo Kang2School of Electronic and Electrical Engineering, Hongik University, Seoul 04066, KoreaDepartment of Civil and Environmental Engineering, Hongik University, Seoul 04066, KoreaSchool of Electronic and Electrical Engineering, Hongik University, Seoul 04066, KoreaNetworks can be used to model various aspects of our lives as well as relations among many real-world entities and objects. To detect a community structure in a network can enhance our understanding of the characteristics, properties, and inner workings of the network. Therefore, there has been significant research on detecting and evaluating community structures in networks. Many fields, including social sciences, biology, engineering, computer science, and applied mathematics, have developed various methods for analyzing and detecting community structures in networks. In this paper, a new community detection algorithm, which repeats the process of dividing a community into two smaller communities by finding a minimum cut, is proposed. The proposed algorithm is applied to some example network data and shows fairly good community detection results with comparable modularity <i>Q</i> values.https://www.mdpi.com/2076-3417/12/12/6218community detectiongraph cutbetweenness centralitymodularity |
| spellingShingle | Hyungsik Shin Jeryang Park Dongwoo Kang A Graph-Cut-Based Approach to Community Detection in Networks Applied Sciences community detection graph cut betweenness centrality modularity |
| title | A Graph-Cut-Based Approach to Community Detection in Networks |
| title_full | A Graph-Cut-Based Approach to Community Detection in Networks |
| title_fullStr | A Graph-Cut-Based Approach to Community Detection in Networks |
| title_full_unstemmed | A Graph-Cut-Based Approach to Community Detection in Networks |
| title_short | A Graph-Cut-Based Approach to Community Detection in Networks |
| title_sort | graph cut based approach to community detection in networks |
| topic | community detection graph cut betweenness centrality modularity |
| url | https://www.mdpi.com/2076-3417/12/12/6218 |
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