Mining Frequent Item Sets for Association Rule Mining in Relational Databases: An Implementation of SETM Algorithm Using Super Market Dataset

D  Kerana Hanirex  and K  P  Kaliyamurthie

doi:10.17485/ijst/2015/v8i31/89006

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Mining Frequent Item Sets for Association Rule Mining in Relational Databases: An Implementation of SETM Algorithm Using Super Market Dataset

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8i31/89006

Year: 2015, Volume: 8, Issue: 31, Pages: 1-5

Original Article

Mining Frequent Item Sets for Association Rule Mining in Relational Databases: An Implementation of SETM Algorithm Using Super Market Dataset

D. Kerana Hanirex^* and K. P. Kaliyamurthie

Department of Computer Science Engineering, Bharath University, Chennai - 600073, Tamil Nadu, India;
[email protected], [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Association rule mining is one of the recent data mining research. Mining frequent itemsets in relational databases using relational queries give great attention to researchers nowadays. This paper implements set oriented algorithm for mining frequent itemsets in relational databases. In this paper the sort and merge scan algorithm SETM is implemented for super market data set. This paper finds out the frequent itemset and its execution time and the results are compared with the traditional Apriori algorithm.
Keywords: 5-6 words, Drawn from title, Word representing the work.