The Koja Web Mapping Application for Context-sensitive Natural Language Spatial Querying

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dc.citation.volume3385
dc.contributor.authorAflaki N
dc.contributor.authorStock K
dc.contributor.authorJones CB
dc.contributor.authorGuesgen H
dc.contributor.authorFukuzawa Y
dc.contributor.authorMorley J
dc.contributor.editorHu X
dc.contributor.editorHu Y
dc.contributor.editorResch B
dc.contributor.editorKersten J
dc.contributor.editorStock K
dc.coverage.spatialDublin, Ireland
dc.date.accessioned2025-05-21T02:28:54Z
dc.date.available2025-05-21T02:28:54Z
dc.date.finish-date2023-04-02
dc.date.issued2023-01-01
dc.date.start-date2023-04-02
dc.description.abstractThe locations of objects are often described in natural language relative to some other object using vague and context-sensitive spatial relation terms (e.g. theatre near Trafalgar Square). Koja is a web map application that predicts the distance between a location and reference object based on the spatial relation term specified by the user and language and contextual features. That distance is used to retrieve objects of the specified type within a range of the distance. They are displayed through a map interface to make the process more intuitive and user-friendly.
dc.description.confidentialfalse
dc.format.pagination29-35
dc.identifier.citationAflaki N, Stock K, Jones CB, Guesgen H, Fukuzawa Y, Morley J. (2023). The Koja Web Mapping Application for Context-sensitive Natural Language Spatial Querying. Hu X, Hu Y, Resch B, Kersten J, Stock K. CEUR Workshop Proceedings. (pp. 29-35). CEUR Team.
dc.identifier.elements-typec-conference-paper-in-proceedings
dc.identifier.issn1613-0073
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/72924
dc.publisherCEUR Team
dc.publisher.urihttps://ceur-ws.org/Vol-3385/paper5.pdf
dc.rights(c) The author/sen
dc.rights.licenseCC BYen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.source.journalCEUR Workshop Proceedings
dc.source.name-of-conferenceGeoExT 2023: First International Workshop on Geographic Information Extraction from Texts at ECIR 2023
dc.subjectWeb map
dc.subjectlocation description
dc.subjectlinguistic features
dc.subjectspatial relation term
dc.subjectspatial preposition
dc.titleThe Koja Web Mapping Application for Context-sensitive Natural Language Spatial Querying
dc.typeconference
pubs.elements-id461878
pubs.organisational-groupOther
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