Výsledky vyhledávání - "Pensa, R. G."

A Framework for Recommending Multimedia Cultural Visiting Paths

Autor: Bartolini, I., Moscato, V., Pensa, R. G., Penta, A., Picariello, A., Carlo Sansone, Sapino, M. L.

Publikováno v: Scopus-Elsevier

In this work, we present a general framework for Cultural Heritage applications able to uniformly manage heterogeneous multimedia data coming from several web repositories and to provide context- Aware recommendation services in order to generate dyn

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::4448ce67e8a61ba4c34e93eefcb4697b
http://hdl.handle.net/11585/481970

Zobrazit plný text záznamu

Numerical data co-clustering via sum-squared residue minimization and user-defined constraint satisfaction

Autor: Pensa R. G., Boulicaut J.

Publikováno v: The Sixteenth Italian Symposium on Advanced Database Systems, pp. 279–286, Mondello (PA), Italy, 22-25 giugno 2008
info:cnr-pdr/source/autori:Pensa R. G.; Boulicaut J./congresso_nome:The Sixteenth Italian Symposium on Advanced Database Systems/congresso_luogo:Mondello (PA), Italy/congresso_data:22-25 giugno 2008/anno:2008/pagina_da:279/pagina_a:286/intervallo_pagine:279–286

Co-clustering aims at computing a bi-partition that is a collection of co-clusters: each co-cluster is a group of objects associated to a group of attributes and these associations can support interpretations. We consider constrained co-clustering no

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::408e32f827f6e440f6bc00147200b4de
http://www.cnr.it/prodotto/i/91872

Zobrazit plný text záznamu

A constraint-based approach for multispace clustering

Autor: Pensa R. G., Nanni M.

Publikováno v: From Local Patterns to Global Models ECML/PKDD-08 Workshop, Antwerp, Belgium, 15 settembre 2008
info:cnr-pdr/source/autori:Pensa R. G.; Nanni M./congresso_nome:From Local Patterns to Global Models ECML%2FPKDD-08 Workshop/congresso_luogo:Antwerp, Belgium/congresso_data:15 settembre 2008/anno:2008/pagina_da:/pagina_a:/intervallo_pagine

In many applications, a set of objects can be represented by different points of view (universes). Beside numeric, ordinal and nominal features, objects may be represented using spatio-temporal information, sequences, and more complex structures (e.g

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a3c6c41bc07b936852a73951c943cd6c
https://openportal.isti.cnr.it/doc?id=people______::a3c6c41bc07b936852a73951c943cd6c

Zobrazit plný text záznamu

Co-classification sous contraintes par la somme des résidus quadratiques

Autor: Pensa R. G., Boulicaut J.

Publikováno v: Extraction et gestion des connaissances, pp. 655–666, Sophia-Antipolis, France, 29 gennaio-1 febbraio 2008
info:cnr-pdr/source/autori:Pensa R. G.; Boulicaut J./congresso_nome:Extraction et gestion des connaissances/congresso_luogo:Sophia-Antipolis, France/congresso_data:29 gennaio-1 febbraio 2008/anno:2008/pagina_da:655/pagina_a:666/intervallo_pagine:655–666

In many applications, the expert interpretation of co-clustering is easier than for monodimensional clustering. Co-clustering aims at computing a bi-partition or a collection of coclusters: each co-cluster is a group of objects associated to a group

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d1046f5456984042ef0c572123aee651
https://openportal.isti.cnr.it/doc?id=people______::d1046f5456984042ef0c572123aee651

Zobrazit plný text záznamu

Constrained co-clustering of gene expression data

Autor: Pensa R. G., Boulicaut J.

Publikováno v: The 2008 SIAM International Conference on Data Mining, pp. 25–36, Atlanta, GA, 24-26 Aprile 2008
info:cnr-pdr/source/autori:Pensa R. G.; Boulicaut J./congresso_nome:The 2008 SIAM International Conference on Data Mining/congresso_luogo:Atlanta, GA/congresso_data:24-26 Aprile 2008/anno:2008/pagina_da:25/pagina_a:36/intervallo_pagine:25–36

In many applications, the expert interpretation of coclustering is easier than for mono-dimensional clustering. Co-clustering aims at computing a bi-partition that is a collection of co-clusters: each co-cluster is a group of objects associated to a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a04516f8cd8b5b7c6cd2f2693c2c85e7
https://publications.cnr.it/doc/91834

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání