Local density-based similarity matrix construction for spectral clustering
According to local and global consistency characterist points'distribution, a spectral cluster-ing algorithm using local density-based similarity matrix construction was proposed. Firstly, by analyzing distribution characteristics of sample data points, the definition of local density was given...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2013-03-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/thesisDetails#10.3969/j.issn.1000-436x.2013.03.003 |
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| _version_ | 1850211903397167104 |
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| author | Jian WU Zhi-ming CUI Yu-jie SHI Sheng-li SHENG Sheng-rong GONG |
| author_facet | Jian WU Zhi-ming CUI Yu-jie SHI Sheng-li SHENG Sheng-rong GONG |
| author_sort | Jian WU |
| collection | DOAJ |
| description | According to local and global consistency characterist points'distribution, a spectral cluster-ing algorithm using local density-based similarity matrix construction was proposed. Firstly, by analyzing distribution characteristics of sample data points, the definition of local density was given, sorting operation on sample point set from dense to sparse according to sample points'local density was did, and undirected graph in accordance with the designed connection strategy was constructed; then, on the basis of GN algorithm's thinking, a calculation method of weight matrix using edge betweenness was given, and similarity matrix of spectral clustering via data conversion was got; lastly, the class number by appearing position of the first eigengap maximum was determined, and the classification of sample point set in eigenvector space by means of classical cluster g method was realized. By means of artificial simulative data set and UCI data set to carry out the experimental tests, show that the proposed spectral algorithm has better cluster-ing capability. |
| format | Article |
| id | doaj-art-043b190dbed04b5f82416dcdad3904f5 |
| institution | OA Journals |
| issn | 1000-436X |
| language | zho |
| publishDate | 2013-03-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-043b190dbed04b5f82416dcdad3904f52025-08-20T02:09:28ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2013-03-0134142259670565Local density-based similarity matrix construction for spectral clusteringJian WUZhi-ming CUIYu-jie SHISheng-li SHENGSheng-rong GONGAccording to local and global consistency characterist points'distribution, a spectral cluster-ing algorithm using local density-based similarity matrix construction was proposed. Firstly, by analyzing distribution characteristics of sample data points, the definition of local density was given, sorting operation on sample point set from dense to sparse according to sample points'local density was did, and undirected graph in accordance with the designed connection strategy was constructed; then, on the basis of GN algorithm's thinking, a calculation method of weight matrix using edge betweenness was given, and similarity matrix of spectral clustering via data conversion was got; lastly, the class number by appearing position of the first eigengap maximum was determined, and the classification of sample point set in eigenvector space by means of classical cluster g method was realized. By means of artificial simulative data set and UCI data set to carry out the experimental tests, show that the proposed spectral algorithm has better cluster-ing capability.http://www.joconline.com.cn/thesisDetails#10.3969/j.issn.1000-436x.2013.03.003spectral clustering;similarity matrix;local density;undirected graph building;edge betweenness |
| spellingShingle | Jian WU Zhi-ming CUI Yu-jie SHI Sheng-li SHENG Sheng-rong GONG Local density-based similarity matrix construction for spectral clustering Tongxin xuebao spectral clustering;similarity matrix;local density;undirected graph building;edge betweenness |
| title | Local density-based similarity matrix construction for spectral clustering |
| title_full | Local density-based similarity matrix construction for spectral clustering |
| title_fullStr | Local density-based similarity matrix construction for spectral clustering |
| title_full_unstemmed | Local density-based similarity matrix construction for spectral clustering |
| title_short | Local density-based similarity matrix construction for spectral clustering |
| title_sort | local density based similarity matrix construction for spectral clustering |
| topic | spectral clustering;similarity matrix;local density;undirected graph building;edge betweenness |
| url | http://www.joconline.com.cn/thesisDetails#10.3969/j.issn.1000-436x.2013.03.003 |
| work_keys_str_mv | AT jianwu localdensitybasedsimilaritymatrixconstructionforspectralclustering AT zhimingcui localdensitybasedsimilaritymatrixconstructionforspectralclustering AT yujieshi localdensitybasedsimilaritymatrixconstructionforspectralclustering AT shenglisheng localdensitybasedsimilaritymatrixconstructionforspectralclustering AT shengronggong localdensitybasedsimilaritymatrixconstructionforspectralclustering |