An empirical study on CO2 emissions in ASEAN countries
This paper proposes a local feature selection (FS) measure namely, Categorical Descriptor Term (CTD) for text categorization. It is derived based on classic term weighting scheme, TFIDF. The method explicitly chooses feature set for each category by only selecting set of terms from relevant category...
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my.unimas.ir.84782015-08-05T01:54:42Z http://ir.unimas.my/id/eprint/8478/ An empirical study on CO2 emissions in ASEAN countries Bong, Chih How Narayanan, Kulathuramaiyer T Technology (General) This paper proposes a local feature selection (FS) measure namely, Categorical Descriptor Term (CTD) for text categorization. It is derived based on classic term weighting scheme, TFIDF. The method explicitly chooses feature set for each category by only selecting set of terms from relevant category. Although past literatures have suggested that the use of features from irrelevant categories can improve the measure of text categorization, we believe that by incorporating only relevant feature can be highly effective. The experimental comparison is carried out between CTD and five wellknown feature selection measures: Information Gain, Chi-Square, Correlation Coefficient, Odd Ratio and GSS Coefficient. The results also show that our proposed method can perform comparatively well with other FS measures, especially on collection with highly overlapped topics. 2012 Conference or Workshop Item NonPeerReviewed text en http://ir.unimas.my/id/eprint/8478/1/An%20Empirical%20Study%20of%20Feature%20Selection%20for%20Text%20Categorization%20based%20on%20Term%20%28abstract%29.pdf Bong, Chih How and Narayanan, Kulathuramaiyer (2012) An empirical study on CO2 emissions in ASEAN countries. In: International Conference on Statistics in Science, Business, and Engineering (ICSSBE), 2012, 10-12 Sept. 2012, Langkawi. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6396635&tag=1 |
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T Technology (General) Bong, Chih How Narayanan, Kulathuramaiyer An empirical study on CO2 emissions in ASEAN countries |
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This paper proposes a local feature selection (FS) measure namely, Categorical Descriptor Term (CTD) for text categorization. It is derived based on classic term weighting scheme, TFIDF. The method explicitly chooses feature set for each category by only selecting set of terms from relevant category. Although past literatures have suggested that the use of features from irrelevant categories can improve the measure of text categorization, we believe that by incorporating only
relevant feature can be highly effective. The experimental
comparison is carried out between CTD and five wellknown
feature selection measures: Information Gain, Chi-Square, Correlation Coefficient, Odd Ratio and GSS Coefficient. The results also show that our proposed method can perform comparatively well with other FS measures, especially on collection with highly overlapped topics. |
format |
Conference or Workshop Item |
author |
Bong, Chih How Narayanan, Kulathuramaiyer |
author_facet |
Bong, Chih How Narayanan, Kulathuramaiyer |
author_sort |
Bong, Chih How |
title |
An empirical study on CO2 emissions in ASEAN countries |
title_short |
An empirical study on CO2 emissions in ASEAN countries |
title_full |
An empirical study on CO2 emissions in ASEAN countries |
title_fullStr |
An empirical study on CO2 emissions in ASEAN countries |
title_full_unstemmed |
An empirical study on CO2 emissions in ASEAN countries |
title_sort |
empirical study on co2 emissions in asean countries |
publishDate |
2012 |
url |
http://ir.unimas.my/id/eprint/8478/1/An%20Empirical%20Study%20of%20Feature%20Selection%20for%20Text%20Categorization%20based%20on%20Term%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/8478/ http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6396635&tag=1 |
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13.211869 |