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Identificação de Regras de Associação Interessantes Combinando Análises Objetivas e Subjetivas

Roberta Akemi SinoaraSolange Oliveira Rezende

The data mining process aims to obtain valid, novel, useful and understandable knowledge. Therefore, techniques for assisting end users to identify interesting knowledge are important, specially in the case of association task. Algorithms used in association task tend to produce a large number of rules, what makes a manual analysis impracticable. In this context, this paper presents a methodology for identifying interesting association rules using objective and subjective analysis. This methodology is composed of two rule evaluation techniques: objective and subjective evaluation measures and evaluation based on query.

http://www.lbd.dcc.ufmg.br/colecoes/enia/2005/023.pdf

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