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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| Format: | Article |
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Penerbit UTM Press
2016
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| _version_ | 1825804214143549440 |
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| 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 |
| collection | UUM |
| 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. |
| first_indexed | 2024-07-04T06:10:46Z |
| format | Article |
| id | uum-19519 |
| institution | Universiti Utara Malaysia |
| last_indexed | 2024-07-04T06:10:46Z |
| publishDate | 2016 |
| publisher | Penerbit UTM Press |
| record_format | eprints |
| spelling | uum-195192016-11-15T03:59:17Z https://repo.uum.edu.my/id/eprint/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 doi:10.11113/jt.v78.9553 |
| 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 |
| title | 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_short | Text classification using modified multi class association rule |
| title_sort | text classification using modified multi class association rule |
| topic | QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT kamaruddinsitisakira textclassificationusingmodifiedmulticlassassociationrule AT yusofyuhanis textclassificationusingmodifiedmulticlassassociationrule AT husnihusniza textclassificationusingmodifiedmulticlassassociationrule AT alrefaimohammadhayel textclassificationusingmodifiedmulticlassassociationrule |