Categorical term descriptor: a proposed term weighting scheme for feature selection

This paper proposes a term weighting scheme, categorical term descriptor (CTD), for feature selection in automated text categorization. CTD is an adaptation of the term frequency inverse document frequency (TFIDF). We compared the performance of the proposed method against classical methods such as...

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Main Authors: Bong, Chih How, Kulathuramaiyer, Narayanan, Wong, Ting Kiong
Format: Proceeding
Language:English
Published: IEEE 2005
Subjects:
Online Access:http://ir.unimas.my/id/eprint/1196/
http://ir.unimas.my/id/eprint/1196/1/categorical%2Bterm%2Bdescriptor%2B%2BA%2Bproposed%2Bterm%2Bweighting%2Bscheme%2Bfor%2Bfeature%2Bselection%2528abstract%2529.pdf
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author Bong, Chih How
Kulathuramaiyer, Narayanan
Wong, Ting Kiong
author_facet Bong, Chih How
Kulathuramaiyer, Narayanan
Wong, Ting Kiong
author_sort Bong, Chih How
building UNIMAS Institutional Repository
collection Online Access
description This paper proposes a term weighting scheme, categorical term descriptor (CTD), for feature selection in automated text categorization. CTD is an adaptation of the term frequency inverse document frequency (TFIDF). We compared the performance of the proposed method against classical methods such as correlation coefficient, chi-square and information gain using the multinomial naive Bayes and the support vector machine (SVKD) classifiers on the Reuters (10) and Reuters (115) variants of Reuters-21578 dataset.
first_indexed 2025-11-15T05:56:18Z
format Proceeding
id unimas-1196
institution Universiti Malaysia Sarawak
institution_category Local University
language English
last_indexed 2025-11-15T05:56:18Z
publishDate 2005
publisher IEEE
recordtype eprints
repository_type Digital Repository
spelling unimas-11962015-03-24T00:48:35Z http://ir.unimas.my/id/eprint/1196/ Categorical term descriptor: a proposed term weighting scheme for feature selection Bong, Chih How Kulathuramaiyer, Narayanan Wong, Ting Kiong AC Collections. Series. Collected works T Technology (General) This paper proposes a term weighting scheme, categorical term descriptor (CTD), for feature selection in automated text categorization. CTD is an adaptation of the term frequency inverse document frequency (TFIDF). We compared the performance of the proposed method against classical methods such as correlation coefficient, chi-square and information gain using the multinomial naive Bayes and the support vector machine (SVKD) classifiers on the Reuters (10) and Reuters (115) variants of Reuters-21578 dataset. IEEE 2005 Proceeding NonPeerReviewed text en http://ir.unimas.my/id/eprint/1196/1/categorical%2Bterm%2Bdescriptor%2B%2BA%2Bproposed%2Bterm%2Bweighting%2Bscheme%2Bfor%2Bfeature%2Bselection%2528abstract%2529.pdf Bong, Chih How and Kulathuramaiyer, Narayanan and Wong, Ting Kiong (2005) Categorical term descriptor: a proposed term weighting scheme for feature selection. In: 2005 IEEENVlClACM International Conference on Web Intelligence (W1'05).
spellingShingle AC Collections. Series. Collected works
T Technology (General)
Bong, Chih How
Kulathuramaiyer, Narayanan
Wong, Ting Kiong
Categorical term descriptor: a proposed term weighting scheme for feature selection
title Categorical term descriptor: a proposed term weighting scheme for feature selection
title_full Categorical term descriptor: a proposed term weighting scheme for feature selection
title_fullStr Categorical term descriptor: a proposed term weighting scheme for feature selection
title_full_unstemmed Categorical term descriptor: a proposed term weighting scheme for feature selection
title_short Categorical term descriptor: a proposed term weighting scheme for feature selection
title_sort categorical term descriptor: a proposed term weighting scheme for feature selection
topic AC Collections. Series. Collected works
T Technology (General)
url http://ir.unimas.my/id/eprint/1196/
http://ir.unimas.my/id/eprint/1196/1/categorical%2Bterm%2Bdescriptor%2B%2BA%2Bproposed%2Bterm%2Bweighting%2Bscheme%2Bfor%2Bfeature%2Bselection%2528abstract%2529.pdf