Abstract

The 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 modified set oriented algorithm for mining frequent itemsets in relational databases. In this paper, the sort and merge scan algorithm SETM (Houtsma and Swami, IEEE 25–33 (1995)) [1] is implemented for super market data set which is further improved by integrating transaction reduction technique. Our proposed algorithm Improved SETM (ISETM) generate the frequent itemsets from the database and find its execution time. Finally the performance of the algorithm is compared with the traditional Apriori and SETM algorithm.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.