Skip to Main content Skip to Navigation
Conference papers

Uncertainty in Ontology Matching: A Decision Rule-Based Approach

Abstract : Considering the high heterogeneity of the ontologies pub-lished on the web, ontology matching is a crucial issue whose aim is to establish links between an entity of a source ontology and one or several entities from a target ontology. Perfectible similarity measures, consid-ered as sources of information, are combined to establish these links. The theory of belief functions is a powerful mathematical tool for combining such uncertain information. In this paper, we introduce a decision pro-cess based on a distance measure to identify the best possible matching entities for a given source entity.
Complete list of metadatas

Cited literature [14 references]  Display  Hide  Download
Contributor : Arnaud Martin <>
Submitted on : Friday, January 23, 2015 - 7:55:35 AM
Last modification on : Friday, March 6, 2020 - 4:46:02 PM
Document(s) archivé(s) le : Friday, April 24, 2015 - 10:11:09 AM


Files produced by the author(s)



Amira Essaid, Arnaud Martin, Grégory Smits, Boutheina Ben Yaghlane. Uncertainty in Ontology Matching: A Decision Rule-Based Approach. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), Jul 2014, Montpellier, France. pp.46 - 55, ⟨10.1007/978-3-319-08795-5_6⟩. ⟨hal-01108547⟩



Record views


Files downloads