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Effective Pattern Discovery for Text Mining

delete2012-01-01
delete164
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OA
AI
N
Ning Zhong *
Y
Yuefeng Li
S
Sheng‐Tang Wu
DOI:10.1109/TKDE.2010.211delete
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摘要

摘要

En 中文
Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase)-based approaches should perform better than the term-based ones, but many experiments do not support this hypothesis. This paper presents an innovative and effective pattern discovery technique which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance.
Keyword:
Text mining
text classification
pattern mining
pattern evolving
information filtering

期刊

IEEE Transactions on Knowledge and Data Engineering 封面图
IEEE Transactions on Knowledge and Data Engineering
IF:
10.4
论文数:
6.8K
被引数:
3.2W

机构

A
asia university taiwan
学者数:
2.0K
论文数: 2.8K
被引数: 5
B
Beijing University of Technology
学者数:
2.8W
论文数: 2.1W
被引数: 2.7W
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