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dc.contributor.authorTSATCHA, Dieudonné
dc.contributor.author
 hal.structure.identifier
CLARAMUNT, Christophe
13094 Institut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorSAUX, Eric
dc.date.accessioned2014
dc.date.available2016
dc.date.issued2013
dc.date.submitted2014
dc.identifier.isbn978-3-642-32315-7
dc.identifier.urihttp://hdl.handle.net/10985/8758
dc.description.abstractThis paper introduces an algorithm for retrieving semantic information from a maritime corpus. The method is based on Natural Language Processing (NPL) and combines a segmentation of large documents with principles of a conceptual vector model (CVM) and synsets of words. This research is applied to the context of intelligent transport systems and maritime navigation. Based on documents regulating maritime traffic, this approach proposes an aid for navigational decision-making while significantly reducing the number of entities and relations required in the modeling process.
dc.language.isoen
dc.publisherSpringer Berlin Heidelberg
dc.rightsPost-print
dc.subjectNatural language processing
dc.subjectConceptual vector model
dc.subjectSemantics
dc.subjectNavigational decision aid
dc.titleA Modeling Approach for the Extraction of Semantic Information from a Maritime Corpus
ensam.embargo.terms2 Years
dc.identifier.doi10.1007/978-3-642-32316-4_12
dc.typdocCommunication avec acte
dc.localisationCentre de Paris
dc.subject.halInformatique: Recherche d'information
ensam.audienceInternationale
ensam.conference.title15th International Symposium on Advances in Spatial Data Handling (SDH)
ensam.conference.date2012-08
ensam.countryGermany
ensam.title.proceedingProceedings of the 15th International Symposium on Advances in Spatial Data Handling (SDH)
ensam.page175-191
hal.statusunsent


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