Email categorization using support vector machine

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.