Data di Pubblicazione:
2004
Abstract:
We thus introduced such technique in the last version of kDCI, which is level-wise hybrid algorithm. kDCI stores the dataset with an horizontal format to disk during the first iterations. After some iteration the dataset may become small enough (thanks to anti-monotone frequency pruning) to be stored in the main memory in a vertical format, and after that the algorithm goes on performing tid-lists intersections to retrieve itemsets supports, and searches among candidates are not needed anymore. Usually the dataset happens to be small enough at most at the fourth iteration.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Frequent itemsets mining
Elenco autori:
Lucchese, Claudio; Perego, Raffaele
Link alla scheda completa: