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Master thesis

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

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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Master thesis
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https://hal.inria.fr/hal-00954085
Contributor : Marie-Christine Fauvet <>
Submitted on : Friday, February 28, 2014 - 4:12:46 PM
Last modification on : Tuesday, December 8, 2020 - 10:42:35 AM

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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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