Evaluation of Term-based Queries using Possibilistic Ontologies

Loiseau, Yannick; Prade, Henri

doi:10.1007/3-540-31590-x_8

Cited by 13 publications

(2 citation statements)

References 20 publications

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“…Its experiment only deals with the medical domain. Work [20] proposed an approach of using ontologies to compute similarity degrees between terms of queries in multiple-source information systems.…”

Section: Related Workmentioning

confidence: 99%

Semantic web services selection improved by application ontology with multiple concept relations

Wang

Hauswirth

Vitvar

et al. 2008

Proceedings of the 2008 ACM Symposium on Applied Computing

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Being able to determine and quantify the semantic similarity between ontological concepts is a key requirement for the discovery, selection, and composition of semantic web services. Especially concept similarity is calculated between different service ontologies, it is still a problem. In this paper, we propose an ontology-based approach for semantic service selection which takes into account the heterogeneity of service descriptions. The approach is based on an application ontology (AO), which is merged by different service ontologies and constructed as a semantic net with multiple concept relations. Empirically the proposed method is shown to improve the quality of service selection.

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Section: Related Workmentioning

confidence: 99%

Semantic web services selection improved by application ontology with multiple concept relations

Wang

Hauswirth

Vitvar

et al. 2008

Proceedings of the 2008 ACM Symposium on Applied Computing

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“…More recently some interesting approaches have been defined to possibilisticbased information retrieval [16][19] [45].…”

Section: Flexible Information Retrievalmentioning

confidence: 99%

Vagueness and uncertainty in information retrieval

Kraft

Pasi

Bordogna

2006

Proceedings of the 2006 International Workshop on Research Issues in Digital Libraries

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The field of fuzzy information systems has grown and is maturing. In this paper, some applications of fuzzy set theory to information retrieval are described, as well as the more recent outcomes of research in this field. Fuzzy set theory is applied to information retrieval with the main aim being to define flexible systems, i.e., systems that can represent and manage the vagueness and subjectivity which characterizes the process of information representation and retrieval, one of the main objectives of artificial intelligence.

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Fuzzy Logic and Ontology-based Information Retrieval

Baziz¹,

Loiseau²,

Prade³

Studies in Fuzziness and Soft Computing

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Evaluation of Term-based Queries using Possibilistic Ontologies

Cited by 13 publications

References 20 publications

Semantic web services selection improved by application ontology with multiple concept relations

Semantic web services selection improved by application ontology with multiple concept relations

Vagueness and uncertainty in information retrieval

Fuzzy Logic and Ontology-based Information Retrieval

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