A local community detection algorithm based on potential community exploration
Local community detection aims to detect local communities that have expanded from the given node. Because of the convenience of obtaining the local information of the network and nearly linear time complexity, researchers have proposed many local community detection algorithms to discover the commu...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Physics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2023.1114296/full |
| _version_ | 1811170966302097408 |
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| author | Shenglong Wang Jing Yang Xiaoyu Ding Jianpei Zhang Meng Zhao |
| author_facet | Shenglong Wang Jing Yang Xiaoyu Ding Jianpei Zhang Meng Zhao |
| author_sort | Shenglong Wang |
| collection | DOAJ |
| description | Local community detection aims to detect local communities that have expanded from the given node. Because of the convenience of obtaining the local information of the network and nearly linear time complexity, researchers have proposed many local community detection algorithms to discover the community structure of real-world networks and have obtained excellent results. Most existing local community detection algorithms expand from the given node to a community based on an expansion mechanism that can determine the membership of nodes. However, when determining the membership of neighboring nodes of a community, previous algorithms only considered the impact from the current community, but the impact from the potential communities around the node was neglected. As the name implies, a potential community is a community structure hidden in an unexplored network around a node. This paper gives the definition of potential communities of a node for the first time, that is, a series of connected components consisting of the node’s neighbors that are in the unexplored network. We propose a three-stage local expansion algorithm, named LCDPC, that performs Local Community Detection based on Potential Community exploration. First, we search for a suitable node to replace the given node as the seed by calculating the node importance and the node similarity. Second, we form the initial community by combining the seed and its suitable potential community. Finally, the eligible nodes are selected by comparing the similarities between potential communities and the expanding community and nodes and adding them to the initial community for community expansion. The proposed algorithm is compared with eight state-of-the-art algorithms on both real-world networks and artificial networks, and the experimental results show that the performance of the proposed algorithm is better than that of the comparison algorithms and that the application of potential community exploration can help identify the community structure of networks. |
| first_indexed | 2024-04-10T17:05:35Z |
| format | Article |
| id | doaj.art-c61da6baef5549c39c68864586e92eb1 |
| institution | Directory Open Access Journal |
| issn | 2296-424X |
| language | English |
| last_indexed | 2024-04-10T17:05:35Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj.art-c61da6baef5549c39c68864586e92eb12023-02-06T06:01:36ZengFrontiers Media S.A.Frontiers in Physics2296-424X2023-02-011110.3389/fphy.2023.11142961114296A local community detection algorithm based on potential community explorationShenglong Wang0Jing Yang1Xiaoyu Ding2Jianpei Zhang3Meng Zhao4Harbin Engineering University, Harbin, ChinaHarbin Engineering University, Harbin, ChinaChongqing University of Posts and Telecommunications, Chongqing, ChinaHarbin Engineering University, Harbin, ChinaHarbin Engineering University, Harbin, ChinaLocal community detection aims to detect local communities that have expanded from the given node. Because of the convenience of obtaining the local information of the network and nearly linear time complexity, researchers have proposed many local community detection algorithms to discover the community structure of real-world networks and have obtained excellent results. Most existing local community detection algorithms expand from the given node to a community based on an expansion mechanism that can determine the membership of nodes. However, when determining the membership of neighboring nodes of a community, previous algorithms only considered the impact from the current community, but the impact from the potential communities around the node was neglected. As the name implies, a potential community is a community structure hidden in an unexplored network around a node. This paper gives the definition of potential communities of a node for the first time, that is, a series of connected components consisting of the node’s neighbors that are in the unexplored network. We propose a three-stage local expansion algorithm, named LCDPC, that performs Local Community Detection based on Potential Community exploration. First, we search for a suitable node to replace the given node as the seed by calculating the node importance and the node similarity. Second, we form the initial community by combining the seed and its suitable potential community. Finally, the eligible nodes are selected by comparing the similarities between potential communities and the expanding community and nodes and adding them to the initial community for community expansion. The proposed algorithm is compared with eight state-of-the-art algorithms on both real-world networks and artificial networks, and the experimental results show that the performance of the proposed algorithm is better than that of the comparison algorithms and that the application of potential community exploration can help identify the community structure of networks.https://www.frontiersin.org/articles/10.3389/fphy.2023.1114296/fulllocal community detectionseed selectionlocal expansionpotential communitynode similarity |
| spellingShingle | Shenglong Wang Jing Yang Xiaoyu Ding Jianpei Zhang Meng Zhao A local community detection algorithm based on potential community exploration Frontiers in Physics local community detection seed selection local expansion potential community node similarity |
| title | A local community detection algorithm based on potential community exploration |
| title_full | A local community detection algorithm based on potential community exploration |
| title_fullStr | A local community detection algorithm based on potential community exploration |
| title_full_unstemmed | A local community detection algorithm based on potential community exploration |
| title_short | A local community detection algorithm based on potential community exploration |
| title_sort | local community detection algorithm based on potential community exploration |
| topic | local community detection seed selection local expansion potential community node similarity |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2023.1114296/full |
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