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New Technology of Library and Information Service  2009, Vol. Issue (10): 67-70    DOI: 10.11925/infotech.1003-3513.2009.10.12
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Research on the Application of WordNet in Text Clustering
Rao Yanghui1,3  Ye Liang2  Cheng Jie2
1(National Science Library, Chinese Academy of Sciences, Beijing 100190, China)
2(Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China)
3(Graduate University of Chinese Academy of Sciences, Beijing 100049, China)
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To deal with “disaster of dimensionality”, cluster identifying and large-scale problems arising in text clustering algorithm’s applications, a parallel text clustering method is proposed and implemented,which uses WordNet to the dimensionality reduction of the word list and stemming based on POS tagging and WordNet. Comparing with the Porter Stemming method, the experimental results show that this method can substantially reduce the dimension of word list, improve the accuracy and recall rate of the clustering and have a better understanding of each cluster.

Key words WordNet      POS tagging      Text clustering      Parallel K-Means     
Received: 07 September 2009      Published: 25 October 2009


Corresponding Authors: Rao Yanghui     E-mail:
About author:: Rao Yanghui,Ye Liang,Cheng Jie

Cite this article:

Rao Yanghui,Ye Liang,Cheng Jie. Research on the Application of WordNet in Text Clustering. New Technology of Library and Information Service, 2009, (10): 67-70.

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