An Information-Theoretic Framework for High-Order Co-Clustering of Heterogeneous Objects (Contributo in atti di convegno)

Type

• Contributo in atti di convegno (Classe)
• Prodotto della ricerca (Classe)

Label

• An Information-Theoretic Framework for High-Order Co-Clustering of Heterogeneous Objects (Contributo in atti di convegno) (literal)

Anno

• 2006-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.1007/11871842_57 (literal)

Alternative label

• Antonio D. Chiaravalloti; Gianluigi Greco; Antonella Guzzo; Luigi Pontieri (2006)
  An Information-Theoretic Framework for High-Order Co-Clustering of Heterogeneous Objects
  in 17th European Conference on Machine Learning (ECML 2006), Berlin, Germany,, September 18-22, 2006
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Antonio D. Chiaravalloti; Gianluigi Greco; Antonella Guzzo; Luigi Pontieri (literal)

Pagina inizio

• 598 (literal)

Pagina fine

• 605 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

• http://www.springerlink.com/content/d5016q5245p34678/fulltext.pdf (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume

• Machine Learning: ECML 2006, Proceedings (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana

• 4212 (literal)

Note

• DBLP (literal)
• ISI Web of Science (WOS) (literal)
• ACM DL (literal)
• Google Scholar (literal)
• Scopu (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• DEIS, UNICAL, Via P. Bucci 30B, 87036, Rende, Italy; Dept. of Mathematics, UNICAL, Via P. Bucci 30B, 87036, Rende, Italy; DEIS, UNICAL, Via P. Bucci 30B, 87036, Rende, Italy; ICAR, CNR, Via Pietro Bucci 41C, 87036 Rende, Italy (literal)

Titolo

• An Information-Theoretic Framework for High-Order Co-Clustering of Heterogeneous Objects (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

• 978-3-540-45375-8 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume

• Furnkranz, J and Scheffer, T and Spiliopoulou, M (literal)

Abstract

• The high-order co-clustering problem, i.e., the problem of simultaneously clustering several heterogeneous types of domains, is usually faced by minimizing a linear combination of some optimization functions evaluated over pairs of correlated domains, where each weight expresses the reliability/relevance of the associated contingency table. Clearly enough, accurately choosing these weights is crucial to the effectiveness of the co-clustering, and techniques for their automatic tuning are particularly desirable, which are instead missing in the literature. This paper faces this issue by proposing an information-theoretic framework where the co-clustering problem does not need any explicit weighting scheme for combining pairwise objective functions, while a suitable notion of agreement among these functions is exploited. Based on this notion, an algorithm for co-clustering a \"star-structured\" collection of domains is defined. (literal)

Prodotto di

• Gestire, Estrarre Conoscenza e Ragionare sui Dati (ICT.P08.002.001) (Modulo)
• Institute for high performance computing and networking (ICAR) (Istituto)

Autore CNR

• LUIGI PONTIERI (Unità di personale interno)

Insieme di parole chiave

• Keywords of "An Information-Theoretic Framework for High-Order Co-Clustering of Heterogeneous Objects" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute for high performance computing and networking (ICAR) (Istituto)
• Gestire, Estrarre Conoscenza e Ragionare sui Dati (ICT.P08.002.001) (Modulo)

Autore CNR di

• LUIGI PONTIERI (Unità di personale interno)

Insieme di parole chiave di

• Keywords of "An Information-Theoretic Framework for High-Order Co-Clustering of Heterogeneous Objects" (Insieme di parole chiave)