Email categorization using support vector machine
Study on text categorization field contains classification process of text documents into a fixed number of pre-defined categories by user. The objective of this project is to make research on classifying email process based on category using Support Vector Machine software. Among processes will be...
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| Format: | Thesis |
| Language: | en |
| Published: |
2004
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| Online Access: | http://eprints.utm.my/3297/1/MariahMohdDaudMFC2004.pdf http://eprints.utm.my/3297/ |
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| _version_ | 1845470864872570880 |
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| author | Mohd. Daud, Mariah |
| author_facet | Mohd. Daud, Mariah |
| author_sort | Mohd. Daud, Mariah |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Study on text categorization field contains classification process of text documents into a fixed number of pre-defined categories by user. The objective of this project is to make research on classifying email process based on category using Support Vector Machine software. Among processes will be used are read input data email from subject and body, feature extraction, feature selection and classify data using Support Vector Machine (SVM). Feature extraction process involved word stopping and word stemming methods that can reduce the number of dimension of features. Features selection process involved TFIDF method. Effective of classification process has been measured using precision and recall criteria. Result produced from analysis showed that Support Vector Machine is very effective in email classifying process. |
| format | Thesis |
| id | my.utm.eprints-3297 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2004 |
| record_format | eprints |
| spelling | my.utm.eprints-32972018-06-26T07:56:26Z http://eprints.utm.my/3297/ Email categorization using support vector machine Mohd. Daud, Mariah QA75 Electronic computers. Computer science QA76 Computer software Study on text categorization field contains classification process of text documents into a fixed number of pre-defined categories by user. The objective of this project is to make research on classifying email process based on category using Support Vector Machine software. Among processes will be used are read input data email from subject and body, feature extraction, feature selection and classify data using Support Vector Machine (SVM). Feature extraction process involved word stopping and word stemming methods that can reduce the number of dimension of features. Features selection process involved TFIDF method. Effective of classification process has been measured using precision and recall criteria. Result produced from analysis showed that Support Vector Machine is very effective in email classifying process. 2004 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/3297/1/MariahMohdDaudMFC2004.pdf Mohd. Daud, Mariah (2004) Email categorization using support vector machine. Other thesis, Universiti Teknologi Malaysia, Faculty of Computer Science and Information System. |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software Mohd. Daud, Mariah Email categorization using support vector machine |
| title | Email categorization using support vector machine |
| title_full | Email categorization using support vector machine |
| title_fullStr | Email categorization using support vector machine |
| title_full_unstemmed | Email categorization using support vector machine |
| title_short | Email categorization using support vector machine |
| title_sort | email categorization using support vector machine |
| topic | QA75 Electronic computers. Computer science QA76 Computer software |
| url | http://eprints.utm.my/3297/1/MariahMohdDaudMFC2004.pdf http://eprints.utm.my/3297/ |
| url_provider | http://eprints.utm.my/ |