Non-negative and sparse spectral clustering

作者：

Highlights：

• We proved that the spectral clustering is equivalent to NMF.

• Under the NMF framework, we propose nonnegative sparse spectral clustering model.

• We propose several algorithms to solve the proposed models.

• Experiment results on real world data show much better performance.

摘要

Highlights•We proved that the spectral clustering is equivalent to NMF.•Under the NMF framework, we propose nonnegative sparse spectral clustering model.•We propose several algorithms to solve the proposed models.•Experiment results on real world data show much better performance.

论文关键词：Spectral clustering,Non-negative matrix factorization,Ratio cut,Normalized cut,Sparseness

论文评审过程：Received 7 December 2012, Revised 24 April 2013, Accepted 4 July 2013, Available online 16 July 2013.

论文官网地址：https://doi.org/10.1016/j.patcog.2013.07.003