Comparative Study of Various Improved Versions of Apriori Algorithm

  ijett-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2013 by IJETT Journal
Volume-4 Issue-4                       
Year of Publication : 2013
Authors : Shruti Aggarwal , Ranveer Kaur


Shruti Aggarwal , Ranveer Kaur. "Comparative Study of Various Improved Versions of Apriori Algorithm". International Journal of Engineering Trends and Technology (IJETT). V4(4):687-690 Apr 2013. ISSN:2231-5381. published by seventh sense research group


In Data Mining Research, Frequent Item set Mining has been considered an important task. These item sets leads to the generation of Association rules . These rules tell about the presence of one item with respect to the presence of another item in large dataset. There are efficient methods for generating Association Rules from large databases. This paper describes methods for frequent item set mining and various improvem ents in the classical algorithm “Apriori” for frequent item set generation .


[1] Rakesh Agrawal, Ramakrishnan Srikant, Fast Algorithms for Mining Association Rules, Proceedings of the 20th VLDB Conference Santiago, Chile, 1994 .
[2] R akesh Agrawal, Tomasz Imielins ki, Arun Swami , Mining Association Rules between Sets of Items in Large Databases, Proceedings of the 1993 ACM SIGMOD Conference Washington DC, USA, May 1993 .
[3] Anurag Choubey, Ravindra Patel, J.L.Rana, “A Survey of Efficient Algorithms and New Appro ach for Fast Discovery of Freqent itemset for Association Rule Mining”, IJSCE ,ISSN: 2231 - 2307, vol. 1, issue 2,May 2011.
[4] Suhani Nagpal, Improved Apriori Algorithm using logarithmic decoding and pruning , International Journal of Engineering Research and Applications (IJERA) ISSN: 2248 - 9622 , Vol. 2, Issue 3, May - Jun 2012, pp.2569 - 2572 .
[5] Sunil Kumar , Shyam Karanth , Akshay K , Ananth Prabhu,Bharathraj Kumar M, Improved Apr i ori Algorithm Based on bottom upapproach using Probability and Matrix, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 2, No 3, March 2012,ISSN (Online): 1694 - 0814 .
[6] R.Divya , S.Vinod kumar, Survey on AIS, Apriori and FP - Tree Algorithms,International Journal of Computer Science and Management Research,Vol 1 Issue 2 September 2012 .
[7] Jiawei Han, Micheline Kamber. “Data Mining: Concepts and Techniques”, Morgan Kaufmann Publishers, Champaign:CS497JH, fall 2001.
[8] Jiao Yabing, “Research of an Improved Apriori Algorithm in Data Mining Association Rules”, International Journal of Computer and Communication Engineering, Vol. 2, No. 1, January 2013.
[9] Jaishree Singh, Hari Ram, Dr. J.S. Sodhi, ”Improving Efficiency of Apriori Algorithm using Transaction Reduction” International Journal of Scientific and Research Publications, Volume 3, Issue 1, January 2013 ISSN 2250 - 3153
[10] John D. Holt and Soon M. Chung, Efficient Mining of Association Rules in Text Databases, AC M 1999.
[11] Patel Tushar, Panchal Mayur, Ladumor Dhara, Kapadiya Jahanvi, Desai Piyusha, Prajapati Ashish, Prajapati, Research J ournal of Computer and Information technology Sciences, Vol 1,2 - 5, February 2013.

Frequent Item sets, Apriori Algorithm, AIS Algorithm , Association Rule Mining (ARM), Partition Algorithm