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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主要作者: Mohd. Daud, Mariah
格式: Thesis
語言:English
出版: 2004
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在線閱讀:http://eprints.utm.my/id/eprint/3297/1/MariahMohdDaudMFC2004.pdf
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spelling my-utm-ep.32972018-06-26T07:56:26Z Email categorization using support vector machine 2004 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 http://eprints.utm.my/id/eprint/3297/ http://eprints.utm.my/id/eprint/3297/1/MariahMohdDaudMFC2004.pdf application/pdf en public other Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic QA75 Electronic computers
Computer science
QA76 Computer software
spellingShingle QA75 Electronic computers
Computer science
QA76 Computer software
Mohd. Daud, Mariah
Email categorization using support vector machine
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
qualification_level other
author Mohd. Daud, Mariah
author_facet Mohd. Daud, Mariah
author_sort Mohd. Daud, Mariah
title Email categorization using support vector machine
title_short 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_sort email categorization using support vector machine
granting_institution Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department Faculty of Computer Science and Information System
publishDate 2004
url http://eprints.utm.my/id/eprint/3297/1/MariahMohdDaudMFC2004.pdf
_version_ 1747814446100643840