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» Text Categorization Based on Boosting Association Rules
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SEMCO
2008
IEEE
13 years 11 months ago
Text Categorization Based on Boosting Association Rules
Associative classification is a novel and powerful method originating from association rule mining. In the previous studies, a relatively small number of high-quality association...
Yongwook Yoon, Gary Geunbae Lee
HICSS
2000
IEEE
150views Biometrics» more  HICSS 2000»
13 years 9 months ago
An Application of Text Mining: Bibliographic Navigator Powered by Extended Association Rules
In this paper, we discuss the implementation and performance of our developed bibliographic navigator with the text mining. We categorize the different attributes and extend the m...
Minoru Kawahara, Hiroyuki Kawano
KDD
2006
ACM
118views Data Mining» more  KDD 2006»
14 years 5 months ago
Reducing the human overhead in text categorization
Many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from...
Arnd Christian König, Eric Brill
ML
2000
ACM
149views Machine Learning» more  ML 2000»
13 years 4 months ago
BoosTexter: A Boosting-based System for Text Categorization
This work focuses on algorithms which learn from examples to perform multiclass text and speech categorization tasks. Our approach is based on a new and improved family of boosting...
Robert E. Schapire, Yoram Singer
ISCI
2007
122views more  ISCI 2007»
13 years 4 months ago
On the strength of hyperclique patterns for text categorization
The use of association patterns for text categorization has attracted great interest and a variety of useful methods have been developed. However, the key characteristics of patte...
Tieyun Qian, Hui Xiong, Yuanzhen Wang, Enhong Chen