Abstract
Association rule engines typically output a very large set of rules. Despite the fact that association rules are regarded as highly comprehensible and useful for data mining and decision support in fields such as marketing, retail, demographics, among others, lengthy outputs may discourage users from using the technique. In this paper we propose a post-processing methodology and tool for browsing/visualizing large sets of association rules. The method is based on a set of operators that transform sets of rules into sets of rules, allowing focusing on interesting regions of the rule space. Each set of rules can be then seen with different graphical representations. The tool is web-based and uses SVG. Association rules are given in PMML.
This work is supported by the European Union grant IST-1999-11.495 Sol-Eu-Net and the POSI/2001/Class Project sponsored by Fundação Ciência e Tecnologia, FEDER e Programa de Financiamento Plurianual de Unidades de I & D.
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Jorge, A., Poças, J., Azevedo, P. (2002). Post-processing Operators for Browsing Large Sets of Association Rules. In: Lange, S., Satoh, K., Smith, C.H. (eds) Discovery Science. DS 2002. Lecture Notes in Computer Science, vol 2534. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36182-0_43
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DOI: https://doi.org/10.1007/3-540-36182-0_43
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