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» Mining for Useful Association Rules Using the ATMS
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KDD
2006
ACM
118views Data Mining» more  KDD 2006»
14 years 8 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
KDD
2000
ACM
114views Data Mining» more  KDD 2000»
13 years 11 months ago
Learning Prosodic Patterns for Mandarin Speech Synthesis
Higher quality synthesized speech is required for widespread use of text-to-speech (TTS) technology, and prosodic pattern is the key feature that makes synthetic speech sound unna...
Yiqiang Chen, Wen Gao, Tingshao Zhu
COLING
2008
13 years 9 months ago
Looking for Trouble
This paper presents a method for mining potential troubles or obstacles related to the use of a given object. Some example instances of this relation are medicine, side effect and...
Stijn De Saeger, Kentaro Torisawa, Jun'ichi Kazama
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
14 years 8 months ago
Sequential cost-sensitive decision making with reinforcement learning
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Edwin P. D. Pednault, Naoki Abe, Bianca Zadrozny
GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
14 years 1 months ago
Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse
In classification, with an increasing number of variables, the required number of observations grows drastically. In this paper we present an approach to put into effect the maxi...
Gero Szepannek, Claus Weihs