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|Title:||Explorando a técnica de indexação de conjuntos candidatos na mineração de conjuntos freqüentes|
|Other Titles:||Exploring direct counting for frequent itemset mining|
|Keywords:||Ciência da computação; Processo de mineração de dados; Regras de associação relacionais; Computer science|
|Abstract:||During the last ten years, many algorithms have been proposed to mine frequent itemsets. In order to fairly evaluate their behavior, the IEEE/ICDM Workshop on Frequent Itemset Mining Implementations (FIMI03) has been recently organized. According to its analysis, kDCI++ is a state-of-the-art algorithm. However, it can be observed from the FIMI 03 experiments that its efficient behavior does not occur for low minimum supports on sparse databases. Aiming at improving kDCI++ and making it even more competitive, we present the kDCI-3 algorithm. This proposal directly accesses candidates not only in the two initial iterations but specially in the third one, which represents, in general, the highest computational cost of kDCI++ for low minimum supports. Results have shown that kDCI-3 outperforms kDCI++ in the conducted experiments. When compared to other important algorithms, kDCI-3 enlarged the number of times kDCI++ presented the best behavior.|
|Appears in Collections:||TEDE sem arquivo|
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