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Proceedings of 2010 Cross-Strait Conference on Information Science and Technology (CSCIST 2010 E-BOOK)

Qinhuangdao,China,7.9-7.13，2010

ISBN: 978-1-935068-15-0 Scientific Research Publishing, USA

E-Book 840pp Pub. Date: July 2010

Category: Computer Science & Communications

Price: $120

Title: Individualized Automatic Classification of Web Documents
Source: Proceedings of 2010 Cross-Strait Conference on Information Science and Technology (CSCIST 2010 E-BOOK) (pp 410-412)
Author(s): Yihjia Tsai, Department of Computer Science and Information Engineering, Tamkang University, Taipei
Kaun-Yu Chen, Department of Computer Science and Information Engineering, Tamkang University, Taipei
Abstract: This paper applies Na?ve Bayes classifier in designing customized automatic web document classification to systematically collecting massive news articles from the Internet. The proposed news classification system allows users to establish the necessary information classifications based on their own preferences. When the amount of daily news is increasing, this approach enables users to effectively filter through large amount of articles and more focused on interested articles. Performances of the proposed approach are characterized by the recall rate and precision. This system can achieve over 66% recall rate, and over 89% precision rate for a real-world Chinese test database.
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