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Finding short patterns to classify text documents

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conference contribution
posted on 2006-01-01, 00:00 authored by Jiyuan An, Yi-Ping Phoebe Chen
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

History

Pagination

293 - 296

Location

Hong Kong, China

Open access

  • Yes

Start date

2006-12-18

End date

2006-12-22

ISBN-13

9780769527475

ISBN-10

0769527477

Language

eng

Notes

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Publication classification

E1 Full written paper - refereed

Copyright notice

2006 IEEE.

Editor/Contributor(s)

J Liu, B Wah

Title of proceedings

2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 main conference proceedings) : (WI '06) : proceedings : 18-22 December, 2006, Hong Kong, China

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