Abstract:Frequent itemset mining is a well studied and important problem in the datamining community. An abundance of different mining algorithms exists, all with different flavor and characteristics, but almost all suffer from two major shortcomings. First, in general frequent itemset mining algorithms perform exhaustive search over a huge pattern space. Second, most algorithms assume that the input data fits into main memory. The first problem was recently tackled in the work of [2], by direct sampling the required n… Show more
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