Chinese Web Page Classification Based on Vector Space Model

Li Wei; Ling Zhang; Hua Mei Li; Xiao Zhou Chen

doi:10.4028/www.scientific.net/AMR.846-847.1801

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 846-847Chinese Web Page Classification Based on Vector...

Chinese Web Page Classification Based on Vector Space Model

Abstract:

Chinese web page classification has been considered as a hot research area in data mining. In this paper, Chinese web page classification algorithm based on vector space model is proposed. This algorithm makes use of supervised machine learning theory to implement a web page classifier. It combined text frequency and methods for feature extraction and improved traditional TFIDF weighting formula. The results show that the classifier was feasible and effective.

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Periodical:

Advanced Materials Research (Volumes 846-847)

Pages:

1801-1804

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.846-847.1801

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Cite this paper

Online since:

November 2013

Authors:

Li Wei, Ling Zhang, Hua Mei Li, Xiao Zhou Chen*

Keywords:

Algorithm (GA), Feature Extraction, Text, Web Page Classification

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* - Corresponding Author

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