GeoXTag: Relative Spatial Information Extraction and Tagging of Unstructured Text - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

GeoXTag: Relative Spatial Information Extraction and Tagging of Unstructured Text

Résumé

Spatial information has gained more attention in natural language processing tasks in different interdisciplinary domains. Moreover, the spatial information is available in two forms: Absolute Spatial Information (ASI) e.g., Paris, London, and Germany and Relative Spatial Information (RSI) e.g., south of Paris, north Madrid and 80 km from Rome. Therefore, it is challenging to extract RSI from textual data and compute its geotagging. This paper presents two strategies and the associated prototypes to address the following tasks: 1) extraction of relative spatial information from textual data and 2) geotagging of this relative spatial information. Experiments show promising results for RSI extraction and tagging.
Fichier principal
Vignette du fichier
Syed_agile2022.pdf (1.72 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03763549 , version 1 (29-08-2022)

Licence

Paternité

Identifiants

Citer

Mehtab Alam Syed, Elena Arsevska, Mathieu Roche, Maguelonne Teisseire. GeoXTag: Relative Spatial Information Extraction and Tagging of Unstructured Text. 25th AGILE Conference on Geographic Information Science, Jun 2022, Vilnius, Lithuania. pp.1 - 10, ⟨10.5194/agile-giss-3-16-2022⟩. ⟨hal-03763549⟩
44 Consultations
23 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More