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.
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Grudzinski, P., Wojciechowski, M., Zakrzewicz, M. (2006). Partition-Based Approach to Processing Batches of Frequent Itemset Queries. In: Larsen, H.L., Pasi, G., Ortiz-Arroyo, D., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2006. Lecture Notes in Computer Science(), vol 4027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11766254_40
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DOI: https://doi.org/10.1007/11766254_40
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