Title: A new scheme for extracting association rules: market basket analysis case study

Authors: Aiman Moyaid Said; P.D.D. Dominic; Suhaiza Zailani

Addresses: Department of Computer and Information Science, Universiti Teknologi PETRONAS, Tronoh, Perak 31750, Malaysia ' Department of Computer and Information Science, Universiti Teknologi PETRONAS, Tronoh, Perak 31750, Malaysia ' School of Management, Universiti Sains Malaysia, Penang 11800, Malaysia

Abstract: The market basket is defined as an itemset purchased together by a customer on a single visit to a store. The market basket analysis is an influential tool for the implementation of store layout and promotional campaign. Particularly in retailing, it is necessary to discover large baskets, since it deals with thousands of items. Most of the previous studies adopt an apriori-like candidate set generation-and-test approach to analyse the market basket data. Although some algorithms can find large itemsets, they can be inefficient in terms of computational time and memory consumption. The aim of this paper is to present new scheme to discover association rules. In addition, a case study in the retailer market is presented to validate the efficiency of the proposed scheme.

Keywords: association rules; frequent itemsets; store layouts; decision-making; promotion decisions; market basket analysis; customers; single visits; promotional campaigns; retailing; retail trade; shopping; large baskets; a priori-like candidates; generation-and-test approach; computational time; memory consumption; supermarkets; business innovation; business research.

DOI: 10.1504/IJBIR.2012.044256

International Journal of Business Innovation and Research, 2012 Vol.6 No.1, pp.28 - 46

Published online: 12 Dec 2014 *

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