A novel association rule mining based on immune computational intelligence

Authors:
Xuesong Xu;Sichun Wang
Affiliations:
Institute of Management Engineering, Information College of Hunan University of Commerce, Changsha, China;Institute of Management Engineering, Information College of Hunan University of Commerce, Changsha, China
Venue:
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Year:
2010

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Abstract

By inspiration of immune computational intelligence, a novel association rule mining algorithm based immune clonal and cluster was proposed. Aim at the efficiency problem of association rules mining, raw data is regarded as antigen and candidate pattern is regarded as antibody. enhancing the antibody's affinity maturation rate and improving the support of candidate patterns through the cluster competition operation. The simulation and real application illustrate this algorithm can increase the convergence velocity and advance veracity of the association rule, and has the remarkable quality of the global and local research reliability.