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Publication
A scalable algorithm for the market basket analysis
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Authors
Advisor(s)
Abstract(s)
The market basket is defined as an itemset bought together by a customer on a single visit to a store. The market basket analysis is a powerful tool for the implementation of cross-selling strategies. Especially in retailing it is essential to discover large baskets, since it deals with thousands of items. Although some algorithms can find large itemsets, they can be inefficient in terms of computational time. The aim of this paper is to present an algorithm to discover large itemset
patterns for the market basket analysis. In this approach, the condensed data is used
and is obtained by transforming the market basket problem into a maximum-weighted
clique problem. Firstly, the input dataset is transformed into a graph-based structure
and then the maximum-weighted clique problem is solved using a meta-heuristic
approach in order to find the most frequent itemsets. The computational results show
large itemset patterns with good scalability properties.
Description
Keywords
Market basket analysis Frequent itemset mining Maximum-weighted clique
Pedagogical Context
Citation
Cavique, Luís - A scalable algorithm for the market basket analysis. "Journal of Retailing and Consumer Services". ISSN 0969-6989. Vol. 14 , Nº 6 (Nov. 2007), p. 400-407
Publisher
Elsevier