Access Restriction

Author An, J. ♦ Chen, Y.-P.P.
Sponsorship IEEE Comput. Soc. ♦ WIC ♦ ACM
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2006
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword rule generation ♦ depth-first. ♦ Test pattern generators ♦ Information technology ♦ Equations ♦ Support vector machines ♦ Text categorization ♦ Support vector machine classification ♦ breadth-first ♦ Document Categorization ♦ Robustness ♦ Australia ♦ Testing
Abstract Many classification methods have been proposed to find patterns in text documents. However, according to Occam's razor principle, "the explanation of any phenomenon should make as few assumptions as possible", short patterns usually have more explainable and meaningful for classifying text documents. In this paper, we propose a depth-first pattern generation algorithm, which can find out short patterns from text document more effectively, comparing with breadth-first algorithm
Description Author affiliation: Sch. of Inf. Technol., Deakin Univ., Geelong, Vic. (An, J.; Chen, Y.-P.P.)
ISBN 0769527477
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2006-12-18
Publisher Place China
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 194.94 kB
Page Count 4
Starting Page 293
Ending Page 296

Source: IEEE Xplore Digital Library