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.
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Joe, I., Shim, H. (2010). An SMS Spam Filtering System Using Support Vector Machine. In: Kim, Th., Lee, Yh., Kang, BH., Ślęzak, D. (eds) Future Generation Information Technology. FGIT 2010. Lecture Notes in Computer Science, vol 6485. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17569-5_56
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DOI: https://doi.org/10.1007/978-3-642-17569-5_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17568-8
Online ISBN: 978-3-642-17569-5
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