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Data Mining in Market Basket Transaction: An Association Rule Mining Approach

S. O. Abdulsalam, K. S. Adewole, A. G. Akintola, M. A. Hambali Published in Artificial Intelligence

International Journal of Applied Information Systems
Year of Publication: 2014
© 2013 by IJAIS Journal
10.5120/ijais14-451244
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  1. S o Abdulsalam, K s Adewole, A g Akintola and M a Hambali. Article: Data Mining in Market Basket Transaction: An Association Rule Mining Approach. International Journal of Applied Information Systems 7(10):15-20, October 2014. BibTeX

    @article{key:article,
    	author = "S.o. Abdulsalam and K.s. Adewole and A.g. Akintola and M.a. Hambali",
    	title = "Article: Data Mining in Market Basket Transaction: An Association Rule Mining Approach",
    	journal = "International Journal of Applied Information Systems",
    	year = 2014,
    	volume = 7,
    	number = 10,
    	pages = "15-20",
    	month = "October",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Data is one of the valuable resources for organization, and database management systems are gradually becoming ubiquitous in many small and medium scale companies. Although, some of the benefits of database management systems have been explored, however, many companies have not been able to exploit the advantages of gaining business intelligence from their databases. This has led to inadequate business decision making based on the data contained in the databases. In this paper, association rules mining also known as market basket analysis using Apriori algorithm is presented for extracting valuable knowledge embedded in the database of a supermarket. Data representing six (6) distinct products across thirty (30) unique transactions were generated from a well-structured transactional database representing the sales pattern of a supermarket store. The frequencies of purchasing these products were extracted for the above data and different association rules were deduced. It was established from these rules that purchase of one product would invariably lead to the purchase of another product as evident in the association between Apple and Chocolate. The discovered relationship will guide companies in planning marketing and advertising strategies that will help them outshine their competitors.

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Keywords

Data Mining, Association Rule, Market Basket Analysis, Apriori Algorithm