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Automatic web page classification in a dynamic and hierarchical way

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2 Author(s)
Xiaogang Peng ; Comput. Sci., Coll. of Eng. & Sci., Louisiana Tech. Univ., Ruston, LA, USA ; Choi, B.

Automatic classification of web pages is an effective way to deal with the difficulty of retrieving information from the Internet. Although there are many automatic classification algorithms and systems that have been proposed, most of them ignore the conflict between the fixed number of categories and the growing number of web pages going into the system. They also require searching through all existing categories to make any classification. We propose a dynamic and hierarchical classification system that is capable of adding new categories as required, organizing the web pages into a tree structure, and classifying web pages by searching through only one path of the tree structure. Our test results show that our proposed single-path search technique reduces the search complexity and increases the accuracy by 6% comparing to related algorithms. Our dynamic-category expansion technique also achieves satisfying results on adding new categories into our system as required.

Published in:

Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on

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