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» Context-sensitive Learning Methods for Text Categorization
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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
SIGIR
1995
ACM
13 years 12 months ago
Noise Reduction in a Statistical Approach to Text Categorization
This paper studies noise reduction for computational efficiency improvements in a statistical learning method for text categorization, the Linear Least Squares Fit (LLSF) mapping...
Yiming Yang
ERCIMDL
2001
Springer
122views Education» more  ERCIMDL 2001»
14 years 28 days ago
Fusion Approaches for Mappings between Heterogeneous Ontologies
Ordering principles of digital libraries expressed in ontologies may be highly heterogeneous even within a domain and especially over different cultures. Automatic methods for mapp...
Thomas Mandl, Christa Womser-Hacker
ECIR
2003
Springer
13 years 9 months ago
Discretizing Continuous Attributes in AdaBoost for Text Categorization
Abstract. We focus on two recently proposed algorithms in the family of “boosting”-based learners for automated text classification, AdaBoost.MH and AdaBoost.MHKR . While the ...
Pio Nardiello, Fabrizio Sebastiani, Alessandro Spe...
AIRS
2004
Springer
14 years 1 months ago
Automatic Word Clustering for Text Categorization Using Global Information
This paper presents a cluster-based text categorization system which uses class distributional clustering of words. We propose a new clustering model which considers the global in...
Wenliang Chen, Xingzhi Chang, Huizhen Wang, Jingbo...