Information retrieval and machine learning for probabilistic schema matching (Contributo in atti di convegno)

Type

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

Label

• Information retrieval and machine learning for probabilistic schema matching (Contributo in atti di convegno) (literal)

Anno

• 2005-01-01T00:00:00+01:00 (literal)

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

• 10.1145/1099554.1099634 (literal)

Alternative label

• Nottelmann H.; Straccia U. (2005)
  Information retrieval and machine learning for probabilistic schema matching
  in 14th ACM Conference on Information and Knowledge Management (CIKM-05), Bremen
  (literal)

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

• Nottelmann H.; Straccia U. (literal)

Pagina inizio

• 295 (literal)

Pagina fine

• 296 (literal)

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

• http://dl.acm.org/citation.cfm?doid=1099554.1099634 (literal)

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

• (Germany, November 2005). Proceedings, pp. 295--296. ACM, 2005. (literal)

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

• ABSTRACT: Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas. This paper presents a probabilistic framework, called sPLMap, for automatically learning schema mapping rules. Similar to LSD, different techniques, mostly from the IR field, are combined. Our approach, however, is also able to give a probabilistic interpretation of the prediction weights of the candidates, and to select the rule set with highest matching probability. (literal)

Note

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

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

• University of Dortmund;ISTI-CNR (literal)

Titolo

• Information retrieval and machine learning for probabilistic schema matching (literal)

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

• 1-59593-140-6 (literal)

Abstract

• Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas. This paper presents a probabilistic framework, called sPLMap, for automatically learning schema mapping rules. Similar to LSD, different techniques, mostly from the IR field, are combined.Our approach, however, is also able to give a probabilistic interpretation of the prediction weights of the candidates, and to select the rule set with highest matching probability. (literal)

Editore

• ACM, Association for computing machinery (Editore)

Prodotto di

• Digital Libraries (ICT.P08.010.002) (Modulo)
• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)

Autore CNR

• UMBERTO STRACCIA (Persona)

Insieme di parole chiave

• Parole chiave di "Information retrieval and machine learning for probabilistic schema matching" (Insieme di parole chiave)

Incoming links:

Autore CNR di

• UMBERTO STRACCIA (Persona)

Prodotto

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Digital Libraries (ICT.P08.010.002) (Modulo)

Editore di

• ACM, Association for computing machinery (Editore)

Insieme di parole chiave di

• Parole chiave di "Information retrieval and machine learning for probabilistic schema matching" (Insieme di parole chiave)