Hierarchical Model-Based Co-Clustering of High-Dimensional Data (Contributo in atti di convegno)

Type
Label
  • Hierarchical Model-Based Co-Clustering of High-Dimensional Data (Contributo in atti di convegno) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Alternative label
  • Gianni Costa; Francesco Folino; Giuseppe Manco; Riccardo Ortale (2007)
    Hierarchical Model-Based Co-Clustering of High-Dimensional Data
    in 15th Italian Symposium on Advanced Database Systems (SEBD 2007)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Gianni Costa; Francesco Folino; Giuseppe Manco; Riccardo Ortale (literal)
Pagina inizio
  • 88 (literal)
Pagina fine
  • 99 (literal)
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto di calcolo e reti ad alte prestazioni; Istituto di calcolo e reti ad alte prestazioni; Istituto di calcolo e reti ad alte prestazioni; Istituto di calcolo e reti ad alte prestazioni (literal)
Titolo
  • Hierarchical Model-Based Co-Clustering of High-Dimensional Data (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-88-902981-0-3 (literal)
Abstract
  • We propose a hierarchical, model-based co-clustering framework for handling high-dimensional datasets. The technique views the dataset as a joint probability distribution over row and column variables. Our approach starts by initially clustering rows in a dataset, where each cluster is characterized by a different probability distribution. Subsequently, the conditional distribution of attributes over tuples is exploited to discover co-clusters underlying the data. An intensive empirical evaluation confirms the effectiveness of our approach, even when compared to well-known co-clustering schemes available from the current literature. (literal)
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