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A Note on Spectral Clustering Method Based on Normalized Cut Criterion
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文献类型:会议论文
标题:A Note on Spectral Clustering Method Based on Normalized Cut Criterion
作者:Sumuya[1];Guo, Chonghui[1];Chai, Shanglei[1]
机构:
年:2009
通讯作者:Sumuya (reprint author), Dalian Univ Technol, Inst Syst Engn, Dalian 116024, Peoples R China.
会议名称:Chinese Conference on Pattern Recognition/1st CJK Joint Workshop on Pattern Recognition
会议论文集:PROCEEDINGS OF THE 2009 CHINESE CONFERENCE ON PATT
页码范围:799-803
会议地点:Nanjing, PEOPLES R CHINA
会议开始日期:2009-11-04
收录情况:EI(20100412657181)  CPCI-S(WOS:000278039800164)  Scopus(2-s2.0-74549212697)  
所属部门:经济管理学院
人气指数:146
浏览次数:146
语言:外文
关键词:spectral clustering method; normalized cut criterion; eigenvalue; eigenvector; indicator vector
摘要:Recently spectral clustering has become one of the most popular clustering algorithms. Although it has many advantages, it still has a lot of shortcomings which should be resolved, such as there are a wide variety of spectral clustering algorithms that use the eigenvectors in slightly different ways and many of these algorithms have no proof that they will actually compute a reasonable clustering. The spectral clustering method based on normalized cut criterion is a very efficient spectral clustering method. In this paper, we give a note on why we choose the first k eigenvectors in the algorithm (rationality of the clustering) and the conditions for indicator vectors under which the clustering problem could lead to the problem of minimizing the objective function of the spectral clustering method based on normalized cut criterion.
全文链接:DOI百度学术
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