DocumentCode
3249581
Title
Automatic web page classification in a dynamic and hierarchical way
Author
Peng, Xiaogang ; Choi, Ben
Author_Institution
Comput. Sci., Coll. of Eng. & Sci., Louisiana Tech. Univ., Ruston, LA, USA
fYear
2002
fDate
2002
Firstpage
386
Lastpage
393
Abstract
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.
Keywords
Internet; information retrieval; learning (artificial intelligence); Internet; automatic web page classification; dynamic-category expansion technique; information retrieval; tree structure; Classification algorithms; Classification tree analysis; Computer science; Educational institutions; Frequency; Humans; Information retrieval; Internet; Organizing; Web pages;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on
Print_ISBN
0-7695-1754-4
Type
conf
DOI
10.1109/ICDM.2002.1183930
Filename
1183930
Link To Document