Frequent regular itemset mining (Contributo in atti di convegno)

Type
Label
  • Frequent regular itemset mining (Contributo in atti di convegno) (literal)
Anno
  • 2010-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1145/1835804.1835840 (literal)
Alternative label
  • Salvatore Ruggieri (2010)
    Frequent regular itemset mining
    in 16th ACM International Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington D.C., USA, 25-28 July 2010
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Salvatore Ruggieri (literal)
Pagina inizio
  • 263 (literal)
Pagina fine
  • 272 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://dl.acm.org/citation.cfm?doid=1835804.1835840 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 10 (literal)
Note
  • Scopu (literal)
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Dipartimento di Informatica, Università di Pisa (literal)
Titolo
  • Frequent regular itemset mining (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-1-4503-0055-1 (literal)
Abstract
  • Concise representations of frequent itemsets sacrifice readability and direct interpretability by a data analyst of the concise patterns extracted. In this paper, we introduce an extension of itemsets, called regular, with an immediate semantics and interpretability, and a conciseness comparable to closed itemsets. Regular itemsets allow for specifying that an item may or may not be present; that any subset of an itemset may be present; and that any non-empty subset of an itemset may be present. We devise a procedure, called {\bf RegularMine}, for mining a set of regular itemsets that is a concise representation of frequent itemsets. The procedure computes a covering, in terms of regular itemsets, of the frequent itemsets in the class of equivalence of a closed one. We report experimental results on several standard dense and sparse datasets that validate the proposed approach. (literal)
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