An Improved Spectral Clustering Algorithm Using Minimum Maximum Principle

Xiu Fang Xu; Sen Xu; Tian Zhou

doi:10.4028/www.scientific.net/AMM.182-183.1881

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 182-183An Improved Spectral Clustering Algorithm Using...

An Improved Spectral Clustering Algorithm Using Minimum Maximum Principle

Abstract:

In this paper a novel document clustering spectral algorithm is proposed, which uses a minimum maximum principle. Firstly the low dimensional embedding of documents is attained by eigenvalue decomposition, and then a minimum maximum principle is used to get the initial seeds for k-means algorithm. Finally, K-means algorithm is performed to get the clustering results. Experimental results show that the clustering results found by this method is better than traditional clustering algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 182-183)

Pages:

1881-1884

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.182-183.1881

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Online since:

June 2012

Authors:

Xiu Fang Xu, Sen Xu, Tian Zhou

Keywords:

Minimum Maximum Principle, Normalized Mutual Information, Spectral Clustering

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