DocumentCode
493626
Title
A New Spam Short Message Classification
Author
Duan Longzhen ; Li An ; Huang Longjun
Author_Institution
Comput. Dept., Nan Chang Univ., Nan Chang
Volume
2
fYear
2009
fDate
7-8 March 2009
Firstpage
168
Lastpage
171
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ETCS.2009.299
Filename
4959013
Link To Document