kDCI: on using direct count up to the third iteration (Contributo in atti di convegno)

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  • kDCI: on using direct count up to the third iteration (Contributo in atti di convegno) (literal)
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  • 2004-01-01T00:00:00+01:00 (literal)
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  • Lucchese C., Orlando S., Perego R. (2004)
    kDCI: on using direct count up to the third iteration
    in ICDM Workshop on Frequent Itemset Mining Implementations, Brighton, UK
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Lucchese C., Orlando S., Perego R. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • In: ICDM - ICDM Workshop on Frequent Itemset Mining Implementations (Brighton, UK, 1 November 2004). Proceedings, pp. 1 - 1. CEUR-WS.org, 2004. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto
  • 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. (literal)
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  • kDCI: on using direct count up to the third iteration (literal)
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