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Author:

Cai, Y.-Q. (Cai, Y.-Q..) (Scholars:蔡永泉) | Jin, Y.-P. (Jin, Y.-P..) | Ge, A.-S. (Ge, A.-S..) | Zhao, K. (Zhao, K..)

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Abstract:

The short messaging service (SMS) spam was effectively recognized based on the associative classification algorithm, and an algorithm called ACW was proposed. The algorithm generated ordered classification rules with association rules mining method by using the semantic order words. In the experiments, that ACW is better than the traditional associative classification algorithm in the territory of classification of SMS is demonstrated in this paper. ©, 2015, Beijing University of Technology. All right reserved.

Keyword:

Associative classification; SMS spam recognition; Word order

Author Community:

  • [ 1 ] [Cai, Y.-Q.]College of Computer Science, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Jin, Y.-P.]College of Computer Science, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Ge, A.-S.]Lenovo Research & Technology Group, Lenovo Group Limited, Beijing, 100084, China
  • [ 4 ] [Zhao, K.]Lenovo Research & Technology Group, Lenovo Group Limited, Beijing, 100084, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2015

Issue: 7

Volume: 41

Page: 1020-1027

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 16

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