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. © 2010 Springer-Verlag Berlin Heidelberg.
Author supplied keywords
Cite
CITATION STYLE
Joe, I., & Shim, H. (2010). An SMS spam filtering system using support vector machine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6485 LNCS, pp. 577–584). https://doi.org/10.1007/978-3-642-17569-5_56
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
