Abstract
In the context of mining frequent itemsets, numerous strategies have been proposed to push several types of constraints within the most well known algorithms. In this paper, we integrate the recently proposed ExAnte data reduction technique within the FP-growth algorithm. Together, they result in a very efficient frequent itemset mining algorithm that effectively exploits monotone constraints.
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© 2004 Springer-Verlag Berlin Heidelberg
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Bonchi, F., Goethals, B. (2004). FP-Bonsai: The Art of Growing and Pruning Small FP-Trees. In: Dai, H., Srikant, R., Zhang, C. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2004. Lecture Notes in Computer Science(), vol 3056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24775-3_19
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DOI: https://doi.org/10.1007/978-3-540-24775-3_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22064-0
Online ISBN: 978-3-540-24775-3
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