Association Rules Mining Based on the Improved Immune Algorithm

Author

Zhang, Yongqiang ; Bu, Shuyang ; Zhang, Yongjian

Author_Institution

Hebei Univ. of Eng., Handan, China

Volume

2

fYear

2009

fDate

21-22 Nov. 2009

Firstpage

453

Lastpage

456

Abstract

Firstly, in this paper we propose an improved immune algorithm, that is, introduce the Metropolis criterion into the selection operation of immune algorithm, and the Metropolis immune algorithm (MIA) is formed, then we carry out the theoretical analysis and experimental simulation aiming at the performance of the MIA; secondly, we use this algorithm to excavate association rules, and propose a new algorithm of association rule mining, then we can verify that the algorithm is feasible and effective through theoretical analysis and experimental results.

Keywords

artificial immune systems; data mining; database management systems; transaction processing; Metropolis immune algorithm; association rules mining; selection operation; transaction database; Algorithm design and analysis; Association rules; Biology computing; Convergence; Data mining; Immune system; Machine learning algorithms; Performance analysis; Random number generation; Simulated annealing; Association rule mining; Immune algorithm; MIA; Metropolis criterion;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on

Conference_Location

Nanchang

Print_ISBN

978-0-7695-3859-4

Type

conf

DOI

10.1109/IITA.2009.260

Filename

5369516