Mining Predicate Association Rule by Gene Expression Programming

  • Jie Zuo
  • Changjie Tang
  • Tianqing Zhang
Conference paper

DOI: 10.1007/3-540-45703-8_9

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2419)
Cite this paper as:
Zuo J., Tang C., Zhang T. (2002) Mining Predicate Association Rule by Gene Expression Programming. In: Meng X., Su J., Wang Y. (eds) Advances in Web-Age Information Management. WAIM 2002. Lecture Notes in Computer Science, vol 2419. Springer, Berlin, Heidelberg

Abstract

Gene expression programming (GEP) is a new technique in genetic computing introduced in 2001. Association rule mining is a typical task in data mining. In this article, a new concept called Predicate Association (PA) is introduced and a new method to discover PA by GEP, called PAGEP (mining Predicate Association by GEP), is proposed. Main results are: (1) The inherent weaknesses of traditional association (TA) are explored. It is proved that TA is a special case of PA. (2) The algorithms for mining PAR, decoding chromosome and fitness are proposed and implemented. (3) It is also proved that gene decoding procedure always success for any well-defined gene. (4) Extensive experiments are given to demonstrate that PAGEP can discover some association rule that cannot be expressed and discovered by traditional method.

Keywords

Predicate association rule Gene expression programming Chromosome Fitness 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Jie Zuo
    • 1
  • Changjie Tang
    • 1
  • Tianqing Zhang
    • 1
  1. 1.Computer DepartmentSichuan University ChinaChina

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