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Maximal frequent itemsets are one of several condensed representations of frequent itemsets, which store most of the information contained in frequent itemsets using less space, thus being more suitable for stream mining. This paper considers a problem that how to mine maximal frequent itemsets over a stream sliding window. We employ a simple but effective data structure to dynamically maintain the...
Maximal frequent itemsets are one of several condensed representations of frequent itemsets, which store most of the information contained in frequent itemsets using less space. This paper proposes an efficient implementation of maximal frequent itemset mining MG utilizing graphics processing units. Our method employs a single-instruction-multiple-data architecture to accelerate the mining speed with...
Frequent itemsets mining is an important problem in data mining. Frequent closed itemsets mining provides complete and condensed information for frequent pattern analysis thus reduces the memory cost without accuracy loss. More research focus on stream mining with the more application of stream. Stream is fast and unlimited thus data had to be stored in limited memory, how to save running time and...
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