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PRIS
2004
13 years 9 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...
IJON
2006
146views more  IJON 2006»
13 years 8 months ago
Feature selection and classification using flexible neural tree
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
Yuehui Chen, Ajith Abraham, Bo Yang
SIGDIAL
2010
13 years 6 months ago
Towards Semi-Supervised Classification of Discourse Relations using Feature Correlations
Two of the main corpora available for training discourse relation classifiers are the RST Discourse Treebank (RST-DT) and the Penn Discourse Treebank (PDTB), which are both based ...
Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuk...
KBSE
1995
IEEE
13 years 12 months ago
Classification and Retrieval of Reusable Components Using Semantic Features
cation at some level of abstraction, abandoning the semantic information provided by the specification. In this paper, we propose a methodology that ships the overhead of formal re...
John Penix, Phillip Baraona, Perry Alexander
ICML
1999
IEEE
14 years 23 days ago
Feature Engineering for Text Classification
Most research in text classification to date has used a “bag of words” representation in which each feature corresponds to a single word. This paper examines some alternative ...
Sam Scott, Stan Matwin