Abstract
Association rule mining is a technique widely used in the field of data mining, which consists in discovering relationships and/or correlations between the attributes of a database. However, the method brings known problems among which the fact that a large number of association rules may be extracted, not all of them being relevant or interesting for the domain expert. In that context, we propose a practical, interactive and helpful guided approach to visualize, evaluate and compare the extracted rules following a step by step methodology, taking into account the interaction between the industrial domain expert and the data mining expert.
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Potes Ruiz, P.A., Kamsu-Foguem, B., Grabot, B. (2014). An Interactive Approach for the Post-processing in a KDD Process. In: Grabot, B., Vallespir, B., Gomes, S., Bouras, A., Kiritsis, D. (eds) Advances in Production Management Systems. Innovative and Knowledge-Based Production Management in a Global-Local World. APMS 2014. IFIP Advances in Information and Communication Technology, vol 438. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44739-0_12
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DOI: https://doi.org/10.1007/978-3-662-44739-0_12
Publisher Name: Springer, Berlin, Heidelberg
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