Market Basket Analysis using A-Priori Algorithm and FP-Tree Algorithm

Abstract

Market Basket Analysis is used for many applications like online marketing, recommendation engines, information security, etc. Over the past few years, it has been one of the hot topics among research groups as its widely used e-commerce site to recommend related products or arrangements of layouts on the basis of frequently purchased items in supermarkets and fixing consumer index price as per consumer’s demands. In this paper, we have focused on two widely used market basket analysis algorithms i.e. Apriori algorithm and FP-growth algorithm. This paper mainly compares these two algorithms and compares the efficiency on the basis of database sizes, time complexity and space complexity. As a finding of comparison of these two algorithms we discovered that the Apriori algorithm required more time complexity while Fp-growth required more space complexity. Apriori algorithm can be used when there are no time constraints but low space available whereas FP-growth Algorithm used for low time constraint as it uses tree repeatedly to add new types of transactions to reduce time complexity.