Abstract
Frequent itemset mining is one of fundamental data mining problems that shares many similarities with traditional database querying. Hence, several query optimization techniques known from database systems have been successfully applied to frequent itemset queries, including reusing results of previous queries and multi-query optimization. In this paper, we consider a new problem of processing of streams of incoming frequent itemset queries, where like in multi-query optimization a number of queries are executed together and share some of their operations, but unlike in previously considered scenarios, new queries are dynamically being added to the currently processed set of queries.
This work was partially supported by the Polish National Science Center (NCN), Grant No. 2011/01/B/ST6/05169.
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Rokosik, M., Wojciechowski, M. (2015). Efficient Processing of Streams of Frequent Itemset Queries. In: Bassiliades, N., et al. New Trends in Database and Information Systems II. Advances in Intelligent Systems and Computing, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-10518-5_2
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DOI: https://doi.org/10.1007/978-3-319-10518-5_2
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