An improved multi-view spectral clustering based on tissue-like P systems
Abstract Multi-view spectral clustering is one of the multi-view clustering methods widely studied by numerous scholars. The first step of multi-view spectral clustering is to construct the similarity matrix of each view. Consequently, the clustering performance will be greatly affected by the quali...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-20358-6 |
| _version_ | 1798044540468199424 |
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| author | Huijian Chen Xiyu Liu |
| author_facet | Huijian Chen Xiyu Liu |
| author_sort | Huijian Chen |
| collection | DOAJ |
| description | Abstract Multi-view spectral clustering is one of the multi-view clustering methods widely studied by numerous scholars. The first step of multi-view spectral clustering is to construct the similarity matrix of each view. Consequently, the clustering performance will be greatly affected by the quality of the similarity matrix of each view. To solve this problem well, an improved multi-view spectral clustering based on tissue-like P systems is proposed in this paper. The optimal per-view similarity matrix is generated in an iterative manner. In addition, spectral clustering is combined with the symmetric nonnegative matrix factorization method to directly output the clustering results to avoid the secondary operation, such as k-means or spectral rotation. Furthermore, improved multi-view spectral clustering is integrated with the tissue-like P system to enhance the computational efficiency of the multi-view clustering algorithm. Extensive experiments verify the effectiveness of this algorithm over other state-of-the-art algorithms. |
| first_indexed | 2024-04-11T23:05:49Z |
| format | Article |
| id | doaj.art-f10eb524552c4080856c0bbe5607032b |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-11T23:05:49Z |
| publishDate | 2022-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-f10eb524552c4080856c0bbe5607032b2022-12-22T03:58:02ZengNature PortfolioScientific Reports2045-23222022-11-0112111710.1038/s41598-022-20358-6An improved multi-view spectral clustering based on tissue-like P systemsHuijian Chen0Xiyu Liu1Shandong Normal University, Business SchoolShandong Normal University, Business SchoolAbstract Multi-view spectral clustering is one of the multi-view clustering methods widely studied by numerous scholars. The first step of multi-view spectral clustering is to construct the similarity matrix of each view. Consequently, the clustering performance will be greatly affected by the quality of the similarity matrix of each view. To solve this problem well, an improved multi-view spectral clustering based on tissue-like P systems is proposed in this paper. The optimal per-view similarity matrix is generated in an iterative manner. In addition, spectral clustering is combined with the symmetric nonnegative matrix factorization method to directly output the clustering results to avoid the secondary operation, such as k-means or spectral rotation. Furthermore, improved multi-view spectral clustering is integrated with the tissue-like P system to enhance the computational efficiency of the multi-view clustering algorithm. Extensive experiments verify the effectiveness of this algorithm over other state-of-the-art algorithms.https://doi.org/10.1038/s41598-022-20358-6 |
| spellingShingle | Huijian Chen Xiyu Liu An improved multi-view spectral clustering based on tissue-like P systems Scientific Reports |
| title | An improved multi-view spectral clustering based on tissue-like P systems |
| title_full | An improved multi-view spectral clustering based on tissue-like P systems |
| title_fullStr | An improved multi-view spectral clustering based on tissue-like P systems |
| title_full_unstemmed | An improved multi-view spectral clustering based on tissue-like P systems |
| title_short | An improved multi-view spectral clustering based on tissue-like P systems |
| title_sort | improved multi view spectral clustering based on tissue like p systems |
| url | https://doi.org/10.1038/s41598-022-20358-6 |
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