Rule-based text categorization using hierarchical categories

Author

Sasaki, Minoru ; Kita, Kenji

Author_Institution

Fac. of Eng., Tokushima Univ., Japan

Volume

3

fYear

1998

fDate

11-14 Oct 1998

Firstpage

2827

Abstract

Document categorization, which is defined as the classification of text documents into one of several fixed classes or categories, has become important with the explosive growth of the World Wide Web. The goal of the work described here is to automatically categorize Web documents in order to enable effective retrieval of Web information. In this paper, based on the rule learning algorithm RIPPER (for Repeated Incremental Pruning to Produce Error Reduction), we propose an efficient method for hierarchical document categorization

Keywords

classification; data mining; information resources; information retrieval; knowledge based systems; learning (artificial intelligence); Web information retrieval; World Wide Web; document categorization; hierarchical categories; hierarchical document categorization; rule learning algorithm RIPPER; rule-based text categorization; text documents classification; Data mining; Explosives; Filtering; Humans; Learning systems; Painting; Partitioning algorithms; Text categorization; Web sites; World Wide Web;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on

Conference_Location

San Diego, CA

ISSN

1062-922X

Print_ISBN

0-7803-4778-1

Type

conf

DOI

10.1109/ICSMC.1998.725090

Filename

725090