On the equivalence of nonnegative matrix factorization and spectral clustering

Chris Ding; Xiaofeng He; Horst D. Simon

doi:10.1137/1.9781611972757.70

On the equivalence of nonnegative matrix factorization and spectral clustering

Chris Ding
, Xiaofeng He
, Horst D. Simon

Lawrence Berkeley National Laboratory

科研成果: 会议稿件 › 论文 › 同行评审

953 引用（Scopus）

摘要

Current nonnegative matrix factorization (NMF) deals with X = FG ^T type. We provide a systematic analysis and extensions of NMF to the symmetric W = HH^T, and the weighted W = HSH^T. We show that (1) W = HH^T is equivalent to Kernel K-means clustering and the Laplacian-based spectral clustering. (2) X = FG^T is equivalent to simultaneous clustering of rows and columns of a bipartite graph. Algorithms are given for computing these symmetric NMFs.

源语言	英语
页	606-610
页数	5
DOI	https://doi.org/10.1137/1.9781611972757.70
出版状态	已出版 - 2005
已对外发布	是
活动	5th SIAM International Conference on Data Mining, SDM 2005 - Newport Beach, CA, 美国期限: 21 4月 2005 → 23 4月 2005

会议

会议	5th SIAM International Conference on Data Mining, SDM 2005
国家/地区	美国
市	Newport Beach, CA
时期	21/04/05 → 23/04/05

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10.1137/1.9781611972757.70

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AU - Ding, Chris

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AB - Current nonnegative matrix factorization (NMF) deals with X = FG T type. We provide a systematic analysis and extensions of NMF to the symmetric W = HHT, and the weighted W = HSHT. We show that (1) W = HHT is equivalent to Kernel K-means clustering and the Laplacian-based spectral clustering. (2) X = FGT is equivalent to simultaneous clustering of rows and columns of a bipartite graph. Algorithms are given for computing these symmetric NMFs.

UR - https://www.scopus.com/pages/publications/33749255098

U2 - 10.1137/1.9781611972757.70

DO - 10.1137/1.9781611972757.70

M3 - 论文

AN - SCOPUS:33749255098

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T2 - 5th SIAM International Conference on Data Mining, SDM 2005

Y2 - 21 April 2005 through 23 April 2005

ER -

On the equivalence of nonnegative matrix factorization and spectral clustering

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