A Fuzzy Model for Improving Relevance Ranking in Information Retrieval Process
Identifieur interne : 002C08 ( Main/Exploration ); précédent : 002C07; suivant : 002C09A Fuzzy Model for Improving Relevance Ranking in Information Retrieval Process
Auteurs : Olufade Onifade ; Odile Thiery [France] ; Adenike Osofisan [France] ; Gérald Duffing [France]Source :
Abstract
Cet article présente nos idées en termes de recherche d'information utilisant différents modèles en aprticulier reposant sur la logique floue. Cela nous permet de déterminer le degré d'adéquation d'une réponse à une requête.
Url:
Affiliations:
- France
- Grand Est, Lorraine (région)
- Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
Links toward previous steps (curation, corpus...)
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- to stream Hal, to step Curation: 000213
- to stream Hal, to step Checkpoint: 002466
- to stream Main, to step Merge: 002C74
- to stream Main, to step Curation: 002C08
Le document en format XML
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<front><div type="abstract" xml:lang="fr">Cet article présente nos idées en termes de recherche d'information utilisant différents modèles en aprticulier reposant sur la logique floue. Cela nous permet de déterminer le degré d'adéquation d'une réponse à une requête.</div>
</front>
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<li>Lorraine (région)</li>
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</settlement>
<orgName><li>Institut national polytechnique de Lorraine</li>
<li>Université Nancy 2</li>
<li>Université de Lorraine</li>
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