An Improved Spectral Clustering Community Detection Algorithm Based on Probability Matrix
The similarity graphs of most spectral clustering algorithms carry lots of wrong community information. In this paper, we propose a probability matrix and a novel improved spectral clustering algorithm based on the probability matrix for community detection. First, the Markov chain is used to calcul...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2020/4540302 |
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| _version_ | 1849304633852297216 |
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| author | Shuxia Ren Shubo Zhang Tao Wu |
| author_facet | Shuxia Ren Shubo Zhang Tao Wu |
| author_sort | Shuxia Ren |
| collection | DOAJ |
| description | The similarity graphs of most spectral clustering algorithms carry lots of wrong community information. In this paper, we propose a probability matrix and a novel improved spectral clustering algorithm based on the probability matrix for community detection. First, the Markov chain is used to calculate the transition probability between nodes, and the probability matrix is constructed by the transition probability. Then, the similarity graph is constructed with the mean probability matrix. Finally, community detection is achieved by optimizing the NCut objective function. The proposed algorithm is compared with SC, WT, FG, FluidC, and SCRW on artificial networks and real networks. Experimental results show that the proposed algorithm can detect communities more accurately and has better clustering performance. |
| format | Article |
| id | doaj-art-3bbbd8028d7e4546b0aab472d57286f6 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-3bbbd8028d7e4546b0aab472d57286f62025-08-20T03:55:41ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2020-01-01202010.1155/2020/45403024540302An Improved Spectral Clustering Community Detection Algorithm Based on Probability MatrixShuxia Ren0Shubo Zhang1Tao Wu2Department of Computer Science and Technology, Tianjin Polytechnic University, Tianjin 300387, ChinaDepartment of Computer Science and Technology, Tianjin Polytechnic University, Tianjin 300387, ChinaDepartment of Computer Science and Technology, Tianjin Polytechnic University, Tianjin 300387, ChinaThe similarity graphs of most spectral clustering algorithms carry lots of wrong community information. In this paper, we propose a probability matrix and a novel improved spectral clustering algorithm based on the probability matrix for community detection. First, the Markov chain is used to calculate the transition probability between nodes, and the probability matrix is constructed by the transition probability. Then, the similarity graph is constructed with the mean probability matrix. Finally, community detection is achieved by optimizing the NCut objective function. The proposed algorithm is compared with SC, WT, FG, FluidC, and SCRW on artificial networks and real networks. Experimental results show that the proposed algorithm can detect communities more accurately and has better clustering performance.http://dx.doi.org/10.1155/2020/4540302 |
| spellingShingle | Shuxia Ren Shubo Zhang Tao Wu An Improved Spectral Clustering Community Detection Algorithm Based on Probability Matrix Discrete Dynamics in Nature and Society |
| title | An Improved Spectral Clustering Community Detection Algorithm Based on Probability Matrix |
| title_full | An Improved Spectral Clustering Community Detection Algorithm Based on Probability Matrix |
| title_fullStr | An Improved Spectral Clustering Community Detection Algorithm Based on Probability Matrix |
| title_full_unstemmed | An Improved Spectral Clustering Community Detection Algorithm Based on Probability Matrix |
| title_short | An Improved Spectral Clustering Community Detection Algorithm Based on Probability Matrix |
| title_sort | improved spectral clustering community detection algorithm based on probability matrix |
| url | http://dx.doi.org/10.1155/2020/4540302 |
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