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» Soft-Supervised Learning for Text Classification
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JIIS
2002
168views more  JIIS 2002»
13 years 7 months ago
Hidden Markov Models for Text Categorization in Multi-Page Documents
In the traditional setting, text categorization is formulated as a concept learning problem where each instance is a single isolated document. However, this perspective is not appr...
Paolo Frasconi, Giovanni Soda, Alessandro Vullo
LREC
2008
193views Education» more  LREC 2008»
13 years 9 months ago
Eksairesis: A Domain-Adaptable System for Ontology Building from Unstructured Text
This paper describes Eksairesis, a system for learning economic domain knowledge automatically from Modern Greek text. The knowledge is in the form of economic terms and the seman...
Katia Kermanidis, Aristomenis Thanopoulos, Manolis...
KDD
2007
ACM
139views Data Mining» more  KDD 2007»
14 years 8 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih
SIGIR
2002
ACM
13 years 7 months ago
Probabilistic combination of text classifiers using reliability indicators: models and results
The intuition that different text classifiers behave in qualitatively different ways has long motivated attempts to build a better metaclassifier via some combination of classifie...
Paul N. Bennett, Susan T. Dumais, Eric Horvitz
SDM
2008
SIAM
133views Data Mining» more  SDM 2008»
13 years 9 months ago
Semantic Smoothing for Bayesian Text Classification with Small Training Data
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu