An SMS spam filtering system using support vector machine

Abstract

This paper describes a powerful and adaptive spam filtering system for SMS (Short Messaging Service) that uses SVM (Support Vector Machine) and a thesaurus. The system isolates words from sample data using a pre-processing device and integrates meanings of isolated words using a thesaurus, generates features of integrated words through chi-square statistics, and studies these features. The system is realized in a Windows environment and its performance is experimentally confirmed.