Abstract
A promising challenge of data mining, especially for association rules technique, is the incremental mining of association whatever is the trend of the association rules. Recently, some researches were devoted to incremental update of temporal association rules problem. In this paper, we focus on cyclic association rules, a class of temporal association rules. Thus, we introduce a new approach called IUPCAR dedicated to maintaining incrementally the cyclic association rules already extracted. Based on the carried out experimental study, we point out the efficiency of our proposal.
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Ben Ahmed, E. (2010). Incremental Update of Cyclic Association Rules. In: Fyfe, C., Tino, P., Charles, D., Garcia-Osorio, C., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2010. IDEAL 2010. Lecture Notes in Computer Science, vol 6283. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15381-5_47
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DOI: https://doi.org/10.1007/978-3-642-15381-5_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15380-8
Online ISBN: 978-3-642-15381-5
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