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Text classification using modified multi class association rule

This paper presents text classification using a modified Multi Class Association Rule Method.The method is based on Associative Classification which combines classification with association rule discovery. Although previous work proved that Associative Classification produces better classification a...

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Main Authors: Kamaruddin, Siti Sakira, Yusof, Yuhanis, Husni, Husniza, Al Refai, Mohammad Hayel
Format: Article
Published: Penerbit UTM Press 2016
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://repo.uum.edu.my/19519/
http://doi.org/10.11113/jt.v78.9553
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spelling my.uum.repo.195192016-11-15T03:59:17Z http://repo.uum.edu.my/19519/ Text classification using modified multi class association rule Kamaruddin, Siti Sakira Yusof, Yuhanis Husni, Husniza Al Refai, Mohammad Hayel QA75 Electronic computers. Computer science This paper presents text classification using a modified Multi Class Association Rule Method.The method is based on Associative Classification which combines classification with association rule discovery. Although previous work proved that Associative Classification produces better classification accuracy compared to typical classifiers, the study on applying Associative Classification to solve text classification problem are limited due to the common problem of high dimensionality of text data and this will consequently results in exponential number of generated classification rules. To overcome this problem the modified Multi-Class Association Rule Method was enhanced in two stages. In stage one the frequent pattern are represented using a proposed vertical data format to reduce the text dimensionality problem and in stage two the generated rule was pruned using a proposed Partial Rule Match to reduce the number of generated rules. The proposed method was tested on a text classification problem and the result shows that it performed better than the existing method in terms of classification accuracy and number of generated rules. Penerbit UTM Press 2016 Article PeerReviewed Kamaruddin, Siti Sakira and Yusof, Yuhanis and Husni, Husniza and Al Refai, Mohammad Hayel (2016) Text classification using modified multi class association rule. Jurnal Teknologi, 78 (8-2). ISSN 0127-9696 http://doi.org/10.11113/jt.v78.9553 doi:10.11113/jt.v78.9553
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Kamaruddin, Siti Sakira
Yusof, Yuhanis
Husni, Husniza
Al Refai, Mohammad Hayel
Text classification using modified multi class association rule
description This paper presents text classification using a modified Multi Class Association Rule Method.The method is based on Associative Classification which combines classification with association rule discovery. Although previous work proved that Associative Classification produces better classification accuracy compared to typical classifiers, the study on applying Associative Classification to solve text classification problem are limited due to the common problem of high dimensionality of text data and this will consequently results in exponential number of generated classification rules. To overcome this problem the modified Multi-Class Association Rule Method was enhanced in two stages. In stage one the frequent pattern are represented using a proposed vertical data format to reduce the text dimensionality problem and in stage two the generated rule was pruned using a proposed Partial Rule Match to reduce the number of generated rules. The proposed method was tested on a text classification problem and the result shows that it performed better than the existing method in terms of classification accuracy and number of generated rules.
format Article
author Kamaruddin, Siti Sakira
Yusof, Yuhanis
Husni, Husniza
Al Refai, Mohammad Hayel
author_facet Kamaruddin, Siti Sakira
Yusof, Yuhanis
Husni, Husniza
Al Refai, Mohammad Hayel
author_sort Kamaruddin, Siti Sakira
title Text classification using modified multi class association rule
title_short Text classification using modified multi class association rule
title_full Text classification using modified multi class association rule
title_fullStr Text classification using modified multi class association rule
title_full_unstemmed Text classification using modified multi class association rule
title_sort text classification using modified multi class association rule
publisher Penerbit UTM Press
publishDate 2016
url http://repo.uum.edu.my/19519/
http://doi.org/10.11113/jt.v78.9553
_version_ 1644282722125873152
score 13.211869

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