We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Call for Paper
December Edition
IJCA solicits high quality original research papers for the upcoming December edition of the journal. The last date of research paper submission is 20 November 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Enhancement of a Data Warehouse Performance using Association Rules Technique

by Walid Moudani, Mohammad Hussein, Mirna Moukhtar, Félix Mora-Camino
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 21 - Number 7
Year of Publication: 2011
Authors: Walid Moudani, Mohammad Hussein, Mirna Moukhtar, Félix Mora-Camino
10.5120/2521-3428

Walid Moudani, Mohammad Hussein, Mirna Moukhtar, Félix Mora-Camino . Enhancement of a Data Warehouse Performance using Association Rules Technique. International Journal of Computer Applications. 21, 7 ( May 2011), 29-37. DOI=10.5120/2521-3428

@article{ 10.5120/2521-3428,
author = { Walid Moudani, Mohammad Hussein, Mirna Moukhtar, Félix Mora-Camino },
title = { Enhancement of a Data Warehouse Performance using Association Rules Technique },
journal = { International Journal of Computer Applications },
issue_date = { May 2011 },
volume = { 21 },
number = { 7 },
month = { May },
year = { 2011 },
issn = { 0975-8887 },
pages = { 29-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume21/number7/2521-3428/ },
doi = { 10.5120/2521-3428 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:07:54.962809+05:30
%A Walid Moudani
%A Mohammad Hussein
%A Mirna Moukhtar
%A Félix Mora-Camino
%T Enhancement of a Data Warehouse Performance using Association Rules Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 21
%N 7
%P 29-37
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The data warehouse holds information management and turns it into meaningful management information, from which, very interesting patterns can be discovered by applying knowledge discovery process. As the update of the Data Warehouse is not too frequent, it is possible to improve query performance while storing the data retrieved by them in a cache. However, the most powerful systems have a small capacity to store the entire database in memory cache. The caching chunks technique is designed to keep in cache the query results in the form of chunks of values, instead of storing them in large tables. In this paper, we propose a new technique for caching multidimensional queries based on association rules. Using this technique will allow all users to enjoy the benefits of Data Warehousing in the best manner, and also to improve performance and also increase the use of the system while reducing the response time. The technique is build using an architecture comprising a data warehouse, a memory cache on the server and a one on each user's machine, in which the association rules and query results are stored. These results are kept in the form of chunks to enjoy all the advantages of the technique of fragmentation into chunks. This approach has been implemented and tested over a real huge data followed by displaying the results and analyzes.

References
  1. Agraval, R. and Srikant, R. 1994. Fast Algorithms for Mining Association Rules. Proc. Of International Conference on Very Large Databases, pp.487-499.
  2. Awad, M. and Latifur, K. 2009. Design and Implementation of data mining tools.
  3. Deshpande, P., Ramasamy, K., Shukla, A., and Naughton, J. 1998. Caching Multidimensional Queries using chunks, SIGMOD Conference.
  4. Fangling, L., Yubin, B., Ge, Y. , Daling, W., and Yuntao, L. 2006. An Efficient Indexing Technique for Computing High Dimensional Data Cubes. Lecture Notes in Computer Science, Springer Berlin, Volume 4016, pp. 557-568.
  5. Hang, K. and Kopriva, 2006. Kernel Based Algorithms For Mining Huge Data Sets, Springer-Verlag.
  6. Keller, A. M., and Basu, J. 1996. A predicate-based caching scheme for client-server database architectures. VLDB Journal, 5(1), pp.35-47.
  7. Kumar, N., Gangopadhyay, A., and Karabatis, G. 2007. Supporting mobile decision making with association rules and multi layered caching. Decision Support Systems, Vol. 43, Issue 1, pp. 16-30.
  8. Inmon, W.H. and Kelly, C. 1993. Developping the Data Warehouse. QED Publishing Group, Boston.
  9. Inmon, W.H. 1997. Building the Data Warehouse. Second Edition, John Wiley and Sons.
  10. Imhoff, C., Galemmo, N., and Geiger, J.G. 2003. Mastering Data Warehouse Design: Relational and Dimensional Techniques. Published by Wiley Publishing, Inc., Indianapolis, Indiana.
  11. Meo, R. and Ceri, S. 1996. A new SQL-like operator for mining association rules. Proc. of 22th International Conf. on Very Large Data Bases, September 3-6, 1996, India.
  12. Pyle, D. and Kaufmann, M. 2003. Business Modeling and Data Mining.
  13. Scheuermann, P., Shim, J., and Vingralek, R. 1996. WATCHMAN: A Data Warehouse Intelligent Cache Manager, Proceedings of the VLDB.
  14. Seshadri, S., Cooper, B.F., and Liu, L. 2005. CubeCache: Efficient and Scalable Processing of OLAP Aggregation Queries in a Peer-to-Peer Network, Proc. of IEEE INFOCOM.
  15. Vercellis, C. 2009. Business Intelligence: Data Mining and Optimization for Decision Making.
  16. Widom, J. 1995. Research Problems in Data Warehouse. Proc. Of the fourth International Conference on Information and knowledge Management, Baltimore, Maryland, pp.25-30.
  17. Witten, I.W. and Eibe F. 2005. Data mining: Practical machine learning tools and techniques.
  18. Ying, F. 2004. Range CUBE: Efficient Cube Computation by Exploiting Data Correlation. Proc. of the 20th ICDE Conference.
  19. Zhao, Y., Deshpande, P., and Naughton, J. 1997. An-array based algorithm for simultaneous Multidimensional aggregates, Proceedins ACM SIGMOD Intl. Conf. on management of Data, p.159-170.
Index Terms

Computer Science
Information Sciences

Keywords

Data Warehouse Data Mining OLAP Association Rules Cache based on chunks

Powered by PhDFocusTM