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 December 2024
Reseach Article

Improved Association Rules Optimization using Modified ABC Algorithm

by Vineet Singh Bhadoriya, Unmukh Dutta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 13
Year of Publication: 2015
Authors: Vineet Singh Bhadoriya, Unmukh Dutta
10.5120/21761-5001

Vineet Singh Bhadoriya, Unmukh Dutta . Improved Association Rules Optimization using Modified ABC Algorithm. International Journal of Computer Applications. 122, 13 ( July 2015), 23-26. DOI=10.5120/21761-5001

@article{ 10.5120/21761-5001,
author = { Vineet Singh Bhadoriya, Unmukh Dutta },
title = { Improved Association Rules Optimization using Modified ABC Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 13 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 23-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number13/21761-5001/ },
doi = { 10.5120/21761-5001 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:59.323641+05:30
%A Vineet Singh Bhadoriya
%A Unmukh Dutta
%T Improved Association Rules Optimization using Modified ABC Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 13
%P 23-26
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To discover the frequent item sets from the huge data sets, one of the most popular techniques of data mining, called association rule mining technique used. For generating association rules from huge database using association rule mining technique, Computer system takes too much. This can be enhanced, if the number of association rules generated using association rule mining technique from a huge dataset can be optimized. So here in this work, firstly association rules are generated using standard Apriori algorithm and then optimized these association rules using modified artificial bee colony (ABC) algorithm. In this modified ABC algorithm, one additional operator, called crossover operator, is used after the third phase, called scout bee phase, of ABC algorithm. Due to the better exploration property of crossover operator, it is used in this work. Experimental results show that the proposed schemes performance better than previously proposed schemes like K-Nearest Neighbor algorithm (KNN) and ABC algorithm.

References
  1. U. Fayyad and R. Uthurusamy, "Data Mining and Knowledge Discovery in Databases", Communications of the ACM, vol. 39, no. 11, 1996, pp. 24–34.
  2. J. Han and M. Kamber, "Data Mining Concepts and Techniques", Morgan Kaufmann, 2006.
  3. W. Soto and A. Olaya-Benavides, "A Genetic Algorithm for Discovery of Association Rules. " In Computer Science Society (SCCC), 2011, pp. 289-293.
  4. X. Yan, C. Zhang and S. Zhang, "Genetic Algorithm- Based Strategy for Identifying Association Rules without Specifying Actual Minimum Support", Expert Systems with Applications, vol. 36, 2009, pp. 3066–3076.
  5. S. N. Sivanandamand and S. N. Deepa, "Introduction to Genetic Algorithms", Springer-Verlag Berlin Heidelberg, 2008.
  6. M. Anandhavalli and S. Kumar Sudhanshu, A. Kumar and M. K. Ghose, "Optimized Association Rule Mining Using Genetic Algorithm", Advances in Information Mining, vol. 1, issue 2, 2009, pp. 01-04.
  7. P. Wakabi-Waiswa and V. Baryamureeba, "Mining High Quality Association Rules using Genetic Algorithms", In Proceedings of the twenty second Midwest Artificial Intelligence and Cognitive Science Conference, 2009, pp. 73-78.
  8. Markus Hegland, "The Apriori Algorithm – a Tutorial", CMA, Australian National University, WSPC/Lecture Notes Series, 22-27. March 30, 2005.
  9. Pujari A. K. , "Data Mining Techniques", Universities Press, 2001.
  10. S. Ghosh, S. Biswas, D. Sarkar and P. P. Sarkar, " Mining Frequent item sets using Genetic Algorithm", international journal of artificial intelligence & applications (IJAIA), Vol. 1, No. 4, October 2010.
  11. Mohit K. Gupta and Geeta Sikka, " Association Rules Extraction using Multi-objective Feature of Genetic Algorihtm", Proceedings of the world congresson engineering & computer science 2013 Vol II, WCECS 2013, 23-25 October- 2013, San Francisco, USA.
  12. Amit Singh, Neetesh Gupta and Amit Sinhal, "Artificial Bee Colony Algorithm with Uniform Mutation", Proceeding of the international conference of soft computing for problem solving (SocPros 2011), Vol. 130, pp 503-511.
  13. Xie, Jiahua. , Yang, Jie. , "A Novel Crossover Operator for Particle Swarm Algorithm ", Machine Vision and Human-Machine Interface (MVHI), 2010 , IEEE Pages 161 – 164.
  14. Vineet S. Bhadoriya and Unmukh Dutta, "Association Rule Optimization using Artificial Bee Colony Algorithm with Crossover" International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-5 Issue-1, March 2015.
Index Terms

Computer Science
Information Sciences

Keywords

Artificial bee colony algorithm ABC Crossover operator Association rules Support Confidence Frequent item sets