A grammar for interpreting geo-analytical questions as concept transformations.

Geographic question answering core concepts of spatial information geo-analytical questions grammatical parser natural language processing

Journal

International journal of geographical information science : IJGIS
ISSN: 1365-8816
Titre abrégé: Int J Geogr Inf Sci
Pays: England
ID NLM: 101086096

Informations de publication

Date de publication:
2023
Historique:
entrez: 23 1 2023
pubmed: 24 1 2023
medline: 24 1 2023
Statut: epublish

Résumé

Geographic Question Answering (GeoQA) systems can automatically answer questions phrased in natural language. Potentially this may enable data analysts to make use of geographic information without requiring any GIS skills. However, going beyond the retrieval of existing geographic facts on particular places remains a challenge. Current systems usually cannot handle geo-analytical questions that require GIS analysis procedures to arrive at answers. To enable

Identifiants

pubmed: 36683723
doi: 10.1080/13658816.2022.2077947
pii: 2077947
pmc: PMC9851665
doi:

Banques de données

figshare
['10.6084/m9.figshare.17009003.v7']

Types de publication

Journal Article

Langues

eng

Pagination

276-306

Informations de copyright

© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Déclaration de conflit d'intérêts

No potential conflict of interest was reported by the author(s).

Références

Trans GIS. 2021 Feb;25(1):424-449
pubmed: 33776542

Auteurs

Haiqi Xu (H)

Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, Netherlands.

Enkhbold Nyamsuren (E)

Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, Netherlands.

Simon Scheider (S)

Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, Netherlands.

Eric Top (E)

Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, Netherlands.

Classifications MeSH