Conceptual Structure Matching using a Bayesian Framework in a Conceptual Indexing. Application to Medical Domain with Multilingual Documents and UMLS Meta-thesaurus

Karam Abdulahhad 1
1 MRIM - Modélisation et Recherche d’Information Multimédia [Grenoble]
LIG - Laboratoire d'Informatique de Grenoble, Inria - Institut National de Recherche en Informatique et en Automatique
Abstract : Information Retrieval Systems that compute a matching between a document and a query based on words intersection, cannot reach relevant documents that do not share any terms with the query. The objective of this master thesis is to propose a solution to this problem in the context of conceptual indexing. We study an ontology based matching that exploit links between concepts. We propose a model that exploits the weighted links of ontology. We also propose to extend the links of the ontology to reflect the structural ambiguity of some concepts. A validation of our proposal is made on the test collection ImagCLEFMed 2005 and the external resource UMLS 2005.
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Mémoires d'étudiants -- Hal-inria+
Information Retrieval [cs.IR]. 2010
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https://hal.inria.fr/hal-00954085
Contributeur : Marie-Christine Fauvet <>
Soumis le : vendredi 28 février 2014 - 16:12:46
Dernière modification le : jeudi 11 octobre 2018 - 08:48:03

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  • HAL Id : hal-00954085, version 1

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Karam Abdulahhad. Conceptual Structure Matching using a Bayesian Framework in a Conceptual Indexing. Application to Medical Domain with Multilingual Documents and UMLS Meta-thesaurus. Information Retrieval [cs.IR]. 2010. 〈hal-00954085〉

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