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Semantic Query Structuring to Enhance Precision of an Information Retrieval System: Application to the Medical Domain

Abstract : Most Information retrieval systems represent a query, also a document, as a bag of indexing terms without any relation between each other. This bag-based representation causes a problem for specialists when they deal with a specific domain like medical one. We present an alternative to the bag of indexing terms representation depending on semantic query structuring, in order to fulfill this need of precision in a specific domain. This structure of a query is obtained by grouping indexing terms using pre-defined categories called dimensions. These dimensions represent the different aspects that could appear in a query or a document. By using this notion, the relevant document to a given query should not only has a maximum number of shared indexing terms but also have a similar structure. Experimental results show precision improvement related to the granularity of dimensions and its distribution over the whole corpus.
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https://hal.inria.fr/hal-00953096
Contributor : Marie-Christine Fauvet <>
Submitted on : Friday, February 28, 2014 - 10:33:07 AM
Last modification on : Thursday, November 19, 2020 - 12:59:40 PM

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  • HAL Id : hal-00953096, version 1

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Mohannad Almasri. Semantic Query Structuring to Enhance Precision of an Information Retrieval System: Application to the Medical Domain. CORIA, 2013, Unknown, pp.293-298. ⟨hal-00953096⟩

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