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» Feature Engineering for Text Classification
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COMPSAC
2005
IEEE
15 years 3 months ago
Recovering "Lack of Words" in Text Categorization for Item Banks
PKIP, Patterned Keywords in Phrase, is our feature selection approach to text categorization (TC) for item banks. An item bank is a collection of textual data in which each item c...
Atorn Nuntiyagul, Nick Cercone, Kanlaya Naruedomku...
79
Voted
KDD
2004
ACM
160views Data Mining» more  KDD 2004»
15 years 10 months ago
Boosting for Text Classification with Semantic Features
Abstract. Current text classification systems typically use term stems for representing document content. Semantic Web technologies allow the usage of features on a higher semantic...
Stephan Bloehdorn, Andreas Hotho
94
Voted
ICML
2005
IEEE
15 years 10 months ago
Generalized LARS as an effective feature selection tool for text classification with SVMs
In this paper we generalize the LARS feature selection method to the linear SVM model, derive an efficient algorithm for it, and empirically demonstrate its usefulness as a featur...
S. Sathiya Keerthi
CORR
2010
Springer
215views Education» more  CORR 2010»
14 years 9 months ago
Text Classification using the Concept of Association Rule of Data Mining
As the amount of online text increases, the demand for text classification to aid the analysis and management of text is increasing. Text is cheap, but information, in the form of...
Chowdhury Mofizur Rahman, Ferdous Ahmed Sohel, Par...
DMIN
2006
114views Data Mining» more  DMIN 2006»
14 years 11 months ago
Towards Using Fewer Features for Text Classification
Abstract-- Text classification or categorization is a conventional classification problem applied to the text domain. In the cases when statistical classification methods are used,...
Yuan Yuan, Tianyang Gu