Deploying Approaches for Pattern Refinement in Text Mining

Wu, Sheng-Tang, Li, Yuefeng, & Xu, Yue (2006) Deploying Approaches for Pattern Refinement in Text Mining. In Sixth International Conference on Data Mining, 2006. ICDM '06, 18-22 December 2006, Hong Kong, China.

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Text mining is the technique that helps users find useful information from a large amount of digital text documents on the Web or databases. Instead of the keyword-based approach which is typically used in this field, the pattern-based model containing frequent sequential patterns is employed to perform the same concept of tasks. However, how to effectively use these discovered patterns is still a big challenge. In this study, we propose two approaches based on the use of pattern deploying strategies. The performance of the pattern deploying algorithms for text mining is investigated on the Reuters dataset RCV1 and the results show that the effectiveness is improved by using our proposed pattern refinement approaches.

Impact and interest:

62 citations in Scopus
29 citations in Web of Science®
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ID Code: 9348
Item Type: Conference Paper
Refereed: No
DOI: 10.1109/ICDM.2006.50
ISBN: 0769527017
ISSN: 1550-4786
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2006 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 05 Sep 2007 00:00
Last Modified: 29 Feb 2012 13:21

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