Abstract
Current approaches to data mining usually address specific userrequests, while no general design criteria for the extraction of associationrules are available for the end-user. In this paper, we propose aclassification of association rule types, which provides a general frameworkfor the design of association rule mining applications. Based on theidentified association rule types, we introduce predefined templates as ameans to capture the user specification of mining applications. Furthermore,we propose a general language to design templates for the extraction ofarbitrary association rule types.
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Baralis, E., Psaila, G. Designing Templates for Mining Association Rules. Journal of Intelligent Information Systems 9, 7–32 (1997). https://doi.org/10.1023/A:1008637019359
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DOI: https://doi.org/10.1023/A:1008637019359