A methodology for identifying interesting association rules by combining objective and subjective measures

• Autores: R. A. Sinoara, S. O. Rezende
• Localización: Inteligencia artificial: Revista Iberoamericana de Inteligencia Artificial, ISSN-e 1988-3064, ISSN 1137-3601, Vol. 10, Nº. 32, 2006, págs. 19-27
• Idioma: español
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• Resumen

  • Evaluation measures, objective and subjective, are used to assist users in finding interesting association rules. Objective measures are more general, but they can be insufficient because they do not consider user's and domain features. However, getting user's knowledge and interest needed to calculate subjective measures can be a difficult task. Thus, this work presents a methodology to identify interesting association rules combining analysis with objective and subjective measures. This methodology aims to use the advantages of each kind of measure and to make user's participation easier. Objective measures are used to select some potentially interesting rules for the user's evaluation. Through this evaluation the user's subjectivity is obtained and used to calculate the subjective measures. Then, the subjective measures assist in identifying the interesting rules. In order to exemplify the methodology application, an experiment was carried out with a real database and the methodology showed to be feasible.