Title :
A New Spam Short Message Classification
Author :
Duan Longzhen ; Li An ; Huang Longjun
Author_Institution :
Comput. Dept., Nan Chang Univ., Nan Chang
Abstract :
This paper proposes an approach of dual-filtering messages. First the combination of KNN classification algorithm and rough set separates spam messages from messages. To avoid lowering precision for reduction, it needs to use KNN classification algorithm to re-filter some messages. This method not only improves the speed of classification but also retains high accuracy based on rough set of KNN classification algorithm.
Keywords :
classification; information filtering; rough set theory; unsolicited e-mail; KNN classification; dual-filtering message; rough set; spam short message classification; Classification algorithms; Computer science education; Educational technology; Filtering; Mobile handsets; Software algorithms; Support vector machine classification; Support vector machines; Telecommunications; Unsolicited electronic mail; KNN; classification; dual-filtering; message; rough set;
Conference_Titel :
Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-1-4244-3581-4
DOI :
10.1109/ETCS.2009.299
