Research and Simulation of Data Mining Method Based on the Association Rules Algorithm

Jin Ping Zou; Xiao Dong Xie

doi:10.4028/www.scientific.net/AMM.651-653.2185

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 651-653Research and Simulation of Data Mining Method...

Research and Simulation of Data Mining Method Based on the Association Rules Algorithm

Abstract:

the accurate data mining problem is studied in this paper. With the increasing of data attributes, degree of complexity of the data storage is also increased, resulting in that in data mining process, the complexity of computation is too high, reducing the convergence of the data mining method, thereby reducing the efficiency of data mining. To this end, this paper presents a data mining method based on association rules algorithm. The data is made simplified processing, to obtain the association rules between data which provides the basis for data mining. According to the association rules between the data, the data in line with the minimum support degree is calculated, to achieve accurate data mining. Experimental results show that the proposed algorithm for data mining, can improve mining efficiency, and achieve the desired results.

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Periodical:

Applied Mechanics and Materials (Volumes 651-653)

Pages:

2185-2188

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.651-653.2185

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Online since:

September 2014

Authors:

Jin Ping Zou*, Xiao Dong Xie

Keywords:

Association Rule, Data Mining (DM), Support Degree

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* - Corresponding Author

References

[1] Xu Zhangyan, Zhang Shichao. An Optimized Apriori Algorithm for Mining Association Rules [J]. Computer engineering, 2003, 29(19): 83-84.

Google Scholar

[2] HAN JIAWEI, PEl JIAN. Mining frequent patterns without candidate generation[C]. Proceedings of the 20th ACM SIGMOD International Conference on Management of Data．New York：ACM, 2000: 1-12.

DOI: 10.1145/342009.335372

Google Scholar

[3] Chen Li, Jiao Licheng. Association rule mining algorithm based on relation Algebra theory [J]. JOURNAL OF NORTHWEST UNIVERSITY (NATURAL SCIENCE EDITION), 2005, 35(6): 692-694.

Google Scholar

[4] BERZAL F, CUBERO J, MARIN N. TBAR: An efficient method for association rule mining in relational databases[J]. Data anti Knowledge Engineering, 2001, 37(1): 47-64.

DOI: 10.1016/s0169-023x(00)00055-0

Google Scholar

[5] Gao Hongbin, Pan Gu, Huang Yiming. Improvement of Apriori algorithm based on characteristic of frequent itemset [J]. COMPUTER ENGINEERING AND DESIGN，2007, 28(10)：2273-2275.

Google Scholar

[6] Yang Xiaoyu, Zhou Peiling, Fu Zhongqian. Immune Analogue and Network Security [J]. Computer simulation, 2001, 20(6): 24-28.

Google Scholar