Abstract
In this paper, we present PRICES, an efficient algorithm for mining association rules, which first identifies all large itemsets and then generates association rules. Our approach reduces large itemset generation time, known to be the most time-consuming step, by scanning the database only once and using logical operations in the process. Experimental results and comparisons with the state of the art algorithm Apriori shows that PRICES very efficient and in some cases up to ten times as fast as Apriori.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Agrawal, R., Imielinski, T., Swami, A.N.: Mining Association Rules between Sets of Items in Large Databases. In: Proceedings of the 1993 ACM SIGMOD Int’l Conf. Management of Data, Washington, D.C., May 1993, pp. 207–216 (1993)
Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules in Large Databases. In: Proc. 20th Int’l Conf. Very Large Data Bases (September 1994)
Dong, L., Tjortjis, C.: Experiences of Using a Quantitative Approach for Mining Association Rules. In: Liu, J., Cheung, Y.-m., Yin, H. (eds.) IDEAL 2003. LNCS, vol. 2690, pp. 693–700. Springer, Heidelberg (2003)
Houtsma, M., Swami, A.: Set-Oriented Mining for Association Rules in Relational Databases. In: Proc. 11th IEEE Int’l Conf. Data Engineering, Taipei, Taiwan, March 1995, pp. 25–34 (1995)
Park, J.S., Chen, M.S., Yu, P.S.: Using a Hash-Based Method with Transaction Trimming For Mining Association Rules. IEEE Transactions on Knowledge and Data Engineering (September/October 1997)
Savasere, A., Omiecinski, E., Navathe, S.B.: An Efficient Algorithm for Mining Association Rules in Large Databases. In: Proc. ACM SIGMOD Int’l Conf. Management of Data, SIGMOD 1998, Seattle, Washington, USA, June 2-4 (1998)
Toivonen, H.: Sampling Large Databases for Association Rules. In: Proc. 22nd Int’l Conf. Very Large Databases, Mumbai, India, pp. 134–145 (1996)
http://www.cs.waikato.ac.nz/~ml/weka Weka Experiment Environment, Weka Data Mining System (Last accessed in March, 2004)
http://www.almaden.ibm.com/software/quest/ Intelligent Information Systems, IBM Almaden Research Center (Last accessed in January, 2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, C., Tjortjis, C. (2004). PRICES: An Efficient Algorithm for Mining Association Rules. In: Yang, Z.R., Yin, H., Everson, R.M. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2004. IDEAL 2004. Lecture Notes in Computer Science, vol 3177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28651-6_52
Download citation
DOI: https://doi.org/10.1007/978-3-540-28651-6_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22881-3
Online ISBN: 978-3-540-28651-6
eBook Packages: Springer Book Archive