Using Apriori with WEKA for Frequent Pattern Mining

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2014 by IJETT Journal
Volume-12 Number-3
Year of Publication : 2014
Authors : Paresh Tanna , Dr. Yogesh Ghodasara


Paresh Tanna , Dr. Yogesh Ghodasara. "Using Apriori with WEKA for Frequent Pattern Mining", International Journal of Engineering Trends and Technology (IJETT), V12(3),127-131 June 2014. ISSN:2231-5381. published by seventh sense research group


Knowledge exploration from the large set of data, generated as a result of the various data processing activities due to data mining only. Frequent Pattern Mining is a very important undertaking in data mining. Apriori approach applied to generate frequent item set generally espouse candidate generation and pruning techniques for the satisfaction of the desired objective. This paper shows how the different approaches achieve the objective of frequent mining along with the complexities required to perform the job. This paper demonstrates the use of WEKA tool for association rule mining using Apriori algorithm.


[1] R. Agrawal and S. Srikant, "Fast Algorithms for Mining Association Rules in Large Databases“, Proceedings of the 20th International Conference on Very Large Data Bases, September 1994.
[2] J. Park, M. Chen and Philip Yu, "An Effective Hash-Based Algorithm for Mining Association Rules", Proceedings of ACM Special Interest Group of Management of Data, ACM SIGMOD’95, 1995.
[3] M. Zaki, S. Parthasarathy, M. Ogihara, and W. Li, "New Algorithms for Fast Discovery of Association Rules", Proc. 3rd ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD`97, Newport Beach, CA), 283-296 AAAI Press, Menlo Park, CA, USA 1997
[4] Shruti Aggarwal, Ranveer Kaur, “Comparative Study of Various Improved Versions of Apriori Algorithm”, International Journal of Engineering Trends and Technology (IJETT) - Volume4Issue4- April 2013
[5] Agrawal, R., T. Imielin´ ski, and A. Swami (1993). "Mining association rules between sets of items in large databases". In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, SIGMOD ’93, New York, NY, USA, pp. 207–216. ACM.
[6] Data Mining: Concepts and Techniques, Jiawei Han and Micheline Kamber, MORGAN KAUFMANN PUBLISHER, An Imprint of Elsevier
[7] Synthetic Data Generation Code for Associations and Sequential Patterns.
[8] Association rule mining with Apriori using WEKA :


Data Mining, Apriori, Frequent Pattern Mining, WEKA.