Universiti Teknologi Malaysia Institutional Repository

Email categorization using support vector machine

Mohd. Daud, Mariah (2004) Email categorization using support vector machine. Other thesis, Universiti Teknologi Malaysia, Faculty of Computer Science and Information System.

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Abstract

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.

Item Type:Thesis (Other)
Additional Information:Project Paper (Sarjana Muda Sains Komputer) - Universiti Teknologi Malaysia, 2004; Supervisor I : Encik Ahmad Fariz bin Ali; Supervisor II : Dr. Ali bin Selamat
Uncontrolled Keywords:software, email
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions:Computer Science and Information System (Formerly known)
ID Code:3297
Deposited By: Dina Amalia Nordin
Deposited On:22 Oct 2007 16:41
Last Modified:26 Jun 2018 15:56

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