Partition-based approach to processing batches of frequent itemset queries

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Abstract

We consider the problem of optimizing processing of batches of frequent itemset queries. The problem is a particular case of multiple-query optimization, where the goal is to minimize the total execution time of the set of queries. We propose an algorithm that is a combination of the Mine Merge method, previously proposed for processing of batches of frequent itemset queries, and the Partition algorithm for memory-based frequent itemset mining. The experiments show that the novel approach outperforms the original Mine Merge and sequential processing in majority of cases. © Springer-Verlag Berlin Heidelberg 2006.

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Grudzinski, P., Wojciechowski, M., & Zakrzewicz, M. (2006). Partition-based approach to processing batches of frequent itemset queries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4027 LNAI, pp. 479–488). Springer Verlag. https://doi.org/10.1007/11766254_40

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