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Fictive motion extraction and classification

hal.structure.identifierDepartment of Geography [Zürich]
dc.contributor.authorEGOROVA, Ekaterina
hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorMONCLA, Ludovic
hal.structure.identifierLaboratoire Informatique de l'Université de Pau et des Pays de l'Adour [LIUPPA]
dc.contributor.authorGAIO, Mauro
hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorCLARAMUNT, Christophe
hal.structure.identifierDepartment of Geography [Zürich]
dc.contributor.authorPURVES, Ross
dc.date.accessioned2021-05-14T09:42:30Z
dc.date.available2021-05-14T09:42:30Z
dc.date.issued2018
dc.identifier.issn1365-8816
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/76741
dc.description.abstractEnFictive motion (e.g. ‘The highway runs along the coast’) is a pervasive phenomenon in language that can imply both a staticand a moving observer. In a corpus of alpine narratives, it is used in three types of spatial descriptions: conveying the actual motion of the observer, describing a vista and communicating encyclopaedic spatial knowledge. This study takes a knowledge-based approach to develop rules for automated extraction and classification of these types based on an annotated corpus of fictive motion instances. In particular, we identify the differences in the set of concepts involved into the production of the three types of descriptions, followed by their linguistic operationalization. Based on that, we build a set of rules that classify fictive motion with an overall precision of 0.87 and recall of 0.71. The article highlights the importance of examining spatially rich, naturally occurring corpora for the lines of work dealing with the automated interpretation of spatial information in texts, as well as, more broadly, investigation of spatial language involved into various types of spatial discourse.
dc.language.isoen
dc.publisherTaylor & Francis
dc.subject.enGIS
dc.subject.enFictive motion
dc.subject.enAutomated extraction
dc.subject.enAutomated classification
dc.subject.enKnowledge-based approach
dc.subject.enNatural Language Processing
dc.title.enFictive motion extraction and classification
dc.typeArticle de revue
dc.identifier.doi10.1080/13658816.2018.1498503
dc.subject.halInformatique [cs]/Informatique et langage [cs.CL]
dc.subject.halInformatique [cs]/Traitement du texte et du document
bordeaux.journalInternational Journal of Geographical Information Science
bordeaux.page2247-2271
bordeaux.volume32
bordeaux.hal.laboratoriesInstitut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295*
bordeaux.issue11
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.institutionINRAE
bordeaux.institutionArts et Métiers
bordeaux.peerReviewedoui
hal.identifierhal-02139019
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02139019v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=International%20Journal%20of%20Geographical%20Information%20Science&rft.date=2018&rft.volume=32&rft.issue=11&rft.spage=2247-2271&rft.epage=2247-2271&rft.eissn=1365-8816&rft.issn=1365-8816&rft.au=EGOROVA,%20Ekaterina&MONCLA,%20Ludovic&GAIO,%20Mauro&CLARAMUNT,%20Christophe&PURVES,%20Ross&rft.genre=article


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