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http://dx.doi.org/10.7840/kics.2013.38B.4.291

An Automatic Web Page Classification System Using Meta-Tag  

Kim, Sang-Il (광운대학교 전자통신공학과)
Kim, Hwa-Sung (광운대학교 전자통신공학과)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.38B, no.4, 2013 , pp. 291-297 More about this Journal
Abstract
Recently, the amount of web pages, which include various information, has been drastically increased according to the explosive increase of WWW usage. Therefore, the need for web page classification arose in order to make it easier to access web pages and to make it possible to search the web pages through the grouping. Web page classification means the classification of various web pages that are scattered on the web according to the similarity of documents or the keywords contained in the documents. Web page classification method can be applied to various areas such as web page searching, group searching and e-mail filtering. However, it is impossible to handle the tremendous amount of web pages on the web by using the manual classification. Also, the automatic web page classification has the accuracy problem in that it fails to distinguish the different web pages written in different forms without classification errors. In this paper, we propose the automatic web page classification system using meta-tag that can be obtained from the web pages in order to solve the inaccurate web page retrieval problem.
Keywords
meta-tag; automatic classification; web page classification; weka naive bayes;
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