Effective pattern taxonomy mining in text documents
Poster
Paper/Presentation Title | Effective pattern taxonomy mining in text documents |
---|---|
Presentation Type | Poster |
Authors | Li, Yuefeng (Author), Wu, Sheng-Tang (Author) and Tao, Xiaohui (Author) |
Editors | Shanahan, James G., Amer-Yahia, Sihem, Zhang, Yi and Kolcz, Alek |
Journal or Proceedings Title | Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM 2008) |
Number of Pages | 2 |
Year | 2008 |
Place of Publication | New York, NY. USA |
ISBN | 9781595939913 |
Digital Object Identifier (DOI) | https://doi.org/10.1145/1458082.1458360 |
Web Address (URL) of Paper | http://dl.acm.org/citation.cfm?doid=1458082.1458360 |
Conference/Event | CIKM 2008: ACM 17th Conference on Information and Knowledge Management |
Event Details | CIKM 2008: ACM 17th Conference on Information and Knowledge Management Event Date 26 to end of 30 Oct 2008 Event Location Napa Valley, United States |
Abstract | Many data mining techniques have been proposed for mining useful patterns in databases. However, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. Most existing methods adopt term-based approaches. However, they all suffer from the problems of polysemy and synonymy. This paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. Substantial experiments on RCV1 demonstrate that the proposed solution achieves encouraging performance. |
Keywords | data mining techniques; existing method; pattern evolving; pattern taxonomy; research issues; text document; text mining |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
461305. Data structures and algorithms | |
460508. Information retrieval and web search | |
Public Notes | Poster paper. |
Byline Affiliations | Queensland University of Technology |
Asia University, Taiwan | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q101w/effective-pattern-taxonomy-mining-in-text-documents
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