Ontology distances for contextualisation - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Reports (Contract/Project Report) Year : 2009

Ontology distances for contextualisation

Abstract

Distances between ontologies are useful for searching, matching or visualising ontologies. We study the various distances that can be defined across ontologies and provide them in a NeOn toolkit plug-in, OntoSim, which is a library of distances that can be used for recontextualising.

Domains

Artificial Intelligence [cs.AI] Discrete Mathematics [cs.DM]
Fichier principal
Vignette du fichier
neon-334.pdf (1.09 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Jérôme Euzenat  : Connect in order to contact the contributor

https://inria.hal.science/hal-00793450

Submitted on : Friday, February 22, 2013-12:32:26 PM

Last modification on : Thursday, April 4, 2024-9:13:21 PM

Long-term archiving on: Sunday, April 2, 2017-4:18:50 AM

Download

Dates and versions

hal-00793450 , version 1 (22-02-2013)

Identifiers

  • HAL Id : hal-00793450 , version 1

Cite

Jérôme Euzenat, Carlo Allocca, Jérôme David, Mathieu d'Aquin, Chan Le Duc, et al.. Ontology distances for contextualisation. [Contract] 2009, pp.50. ⟨hal-00793450⟩

Export

BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite

Collections

UNIV-RENNES1 UGA CNRS INRIA IRISA LIG INRIA2 TDS-MACS LARA UR1-MATH-STIC UR1-UFR-ISTIC UNIV-RENNES UR1-MATH-NUM LIG_SIDCH
245 View
374 Download

Share

Gmail Facebook X LinkedIn More