Spectral clustering for Chinese word

Authors:
Ying Liu;Wang Nan;Tie Zheng
Affiliations:
Department of Chinese Language and Literature, Tsinghua University, Beijing, China;Department of Chinese Language and Literature, Tsinghua University, Beijing, China;Department of Chinese Language and Literature, Tsinghua University, Beijing, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Year:
2009

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Abstract

The similarity between words is used for word clustering. In spectral clustering algorithms, the information contained in the eigenvectors of a affinity matrix is used to detect the similarity. Compared with traditional clustering methods, spectral clustering performs much better for clustering the words especially in multidimensional vector spaces. The spectral clustering is implemented by Visual C++ and Matlab in this paper, which is applied to cluster small scale segmented Chinese corpus and large scale non-segmented Chinese corpus. Good experimental results are observed and result analyses are given for spectral clustering.