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PRIS
2004
13 years 5 months ago
Effect of Feature Smoothing Methods in Text Classification Tasks
Abstract. The number of features to be considered in a text classification system is given by the size of the vocabulary and this is normally in the range of the tens or hundreds o...
David Vilar, Hermann Ney, Alfons Juan, Enrique Vid...
AAAI
2008
13 years 6 months ago
An Effective and Robust Method for Short Text Classification
Classification of texts potentially containing a complex and specific terminology requires the use of learning methods that do not rely on extensive feature engineering. In this w...
Victoria Bobicev, Marina Sokolova
SDM
2008
SIAM
133views Data Mining» more  SDM 2008»
13 years 6 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
SMC
2007
IEEE
133views Control Systems» more  SMC 2007»
13 years 10 months ago
Text classification using multi-word features
—We carried out a series of experiments on text classification using multi-word features. An automated method was proposed to extract the multi-words from text data set and two d...
Wen Zhang, Taketoshi Yoshida, Xijin Tang
ICTAI
2007
IEEE
13 years 10 months ago
Dragon Toolkit: Incorporating Auto-Learned Semantic Knowledge into Large-Scale Text Retrieval and Mining
The majority of text retrieval and mining techniques are still based on exact feature (e.g. words) matching and unable to incorporate text semantics. Many researchers believe that...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu