DocumentCode
3228696
Title
Finding Short Patterns to Classify Text Documents
Author
An, Jiyuan ; Chen, Yi-Ping Phoebe
Author_Institution
Sch. of Inf. Technol., Deakin Univ., Geelong, Vic.
fYear
2006
fDate
18-22 Dec. 2006
Firstpage
293
Lastpage
296
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
Keywords
classification; text analysis; tree searching; Occam razor principle; breadth-first algorithm; depth-first pattern generation algorithm; text document classification; text document pattern finding; Australia; Equations; Information technology; Robustness; Support vector machine classification; Support vector machines; Test pattern generators; Testing; Text categorization; Document Categorization; breadth-first; depth-first.; rule generation;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on
Conference_Location
Hong Kong
Print_ISBN
0-7695-2747-7
Type
conf
DOI
10.1109/WI.2006.82
Filename
4061379
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