Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.2/1951
Título: A scalable algorithm for the market basket analysis
Autor: Cavique, Luís
Palavras-chave: Market basket analysis
Frequent itemset mining
Maximum-weighted clique
Data: 2007
Editora: Elsevier
Citação: 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
Relatório da Série N.º: 6
Resumo: 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.
Peer review: yes
URI: http://hdl.handle.net/10400.2/1951
ISSN: 0969-6989
Versão do Editor: doi:10.1016/j.jretconser.2007.02.003
Aparece nas colecções:Ciências e Tecnologia - Capítulos/artigos em livros internacionais / Book chapters/papers in international books

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
LCv 2007b.pdf127,51 kBAdobe PDFVer/Abrir


FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote Degois 

Todos os registos no repositório estão protegidos por leis de copyright, com todos os direitos reservados.