Efficient similarity search for market basket data

Authors:
Alexandros Nanopoulos;Yannis Manolopoulos
Affiliations:
Department of Informatics, Aristotle University of Thessaloniki, Greece/ e-mail: &lcub/alex,manolopo&rcub/&commat/delab.csd.auth.gr;Department of Informatics, Aristotle University of Thessaloniki, Greece/ e-mail: &lcub/alex,manolopo&rcub/&commat/delab.csd.auth.gr
Venue:
The VLDB Journal — The International Journal on Very Large Data Bases
Year:
2002

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Abstract

Several organizations have developed very large market basket databases for the maintenance of customer transactions. New applications, e.g., Web recommendation systems, present the requirement for processing similarity queries in market basket databases. In this paper, we propose a novel scheme for similarity search queries in basket data. We develop a new representation method, which, in contrast to existing approaches, is proven to provide correct results. New algorithms are proposed for the processing of similarity queries. Extensive experimental results, for a variety of factors, illustrate the superiority of the proposed scheme over the state-of-the-art method.