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A Review Paper on Parallel Association Rules Mining Algorithm in Data Mining and MapReduce Framework

Brijendra Singh, Rohit Miri


Database Technology needed in all the areas. It’s a platform that provides facility to work with data in any digital domain. Data mining is a wide topic in the database world. This paper presented here, talks for data mining issue, Association Rules, the basic algorithm and parallel association rules algorithm for association rules mining in data streams. Study these algorithms and compare them. Also discuss the future scope for better algorithms and for the very large database.


Data Mining, Association Rules, Apriori Algorithm, Parallel Association Rules, Mapreduce Framework.

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Agrawal R, Imielinski T and Swami A., “Mining association rules between sets of items in large database”. In Proc. Of the ACM SIGMOD conference on Management of Data, pp. 207-216, Washington, D.C., May 1993.

Agrawal R, Srikant R (1994) “Fast algorithms for mining association rules”. In: Proceedings of the 20th VLDB conference, pp. 487-499.

Agrawal, R., & Shafer, J. C. (1996).” Parallel mining of association rules”. Knowledge and Data Engineering, IEEE Transactions on, 8(6), pp. 962- 969.

LIN C H,CHill D Y,WU Y H,etal, “Mining frequent itemsets from data streams with a time sensitive sliding window”.Proc of the 5th SIAM International Conference on Data Mining 2005.

JIANG Nan,GRUENW ALD L, “Research issues in data streams association rule mining”. ACM SIGKDD Record.2006, 35(1), pp. 14-19.

H. Mahgoub,"Mining association rules from unstructured documents" in Proc. 3rd Int. Conf. on Knowledge Mining, ICKM, Prague, Czech Republic, Aug. 25- 27, 2006, pp. 167-1 72.

S. Kannan, and R. Bhaskaran "Association rule pruning based on interestingness measures with clustering". International Journal of Computer Science Issues, IJCSI, 6(1), 2009, pp. 35-43.

M. Ashrafi, D. Taniar, and K. Smith "A New Approach of Eliminating Redundant Association Rules". Lecture Notes in Computer Science, Volume 31 S0, 2004, pp. 465-474.

P. Tang, M. Turkia "Parallelizing frequent itemset mining with FPtrees". Technical Report., Department of Computer Science, University of Arkansas at Little Rock, 2005.

M. Ashrafi, D. Taniar, and K. Smith "Redundant Association Rules Reduction Techniques". Lecture Notes in Computer Science, Volume 3S09, 2005, pp. 254 -263.

Gordon, K. (2013). What is Big Data? ITNOW, 55(3), pp. 12-13.

S Pandey, R Miri, SR Tandan (2013) “Diagnosis And Classification Of Hypothyroid Disease Using Data Mining Techniques ” International Journal of Engineering Research and Technology (IJERT).

MK Shrivastava, P Chouksey, R Miri (2013) “Exploring Data Mining Classification Techniques“International Journal of Engineering Research and Technology (IJERT).

J Dongre and G L prajapati, “the Role of Apriori algorithm for Finding the Association Rules in Data Mining” International Conference on Issue and Challenges in Intelligent Computing Techniques(ICICT) IEEE 2014, pp. 657-660.

Hua wang, Ping Liu, Hongyang Li, “Application of Improved Association Rule Algorithm in the Course Management” IEEE 2014, pp. 804-807.

J. han, M. Kamber and J. Pei, “Data Mining: Concept and Techniques” 3rd ed. San Francisco, 2011.

Shibbir A, Rajshekhar P and Abu S M L H, “Knowledge discovery from academic data using association rule mining” 2014 17th International conference on computer and information technology (ICCIT) IEEE 2014, pp. 314-319.


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