Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, Epiciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Journal articles

Geoparsing and geocoding places in a dynamic space context: The case of hiking descriptions

Mauro Gaio 1 Ludovic Moncla 2 
2 DM2L - Data Mining and Machine Learning
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : The backbone of the proposal in this chapter is an automatic parser and a formal encoder of information describing places, spatial and verbal relations in textual documents in order to reconstruct and map the textually described itinerary. These tools allow us to show how to combine the information expressed in French texts, referring to places, spatial actions associated with them, and data found in external geographical resources to build a geocoded representation of an itinerary. Our approach focuses on the automatic reconstruction of routes and transcribes them in their geographical setting, identifying locations and routes by interpreting spatial information in a dynamic space context.
Complete list of metadata
Contributor : Ludovic Moncla Connect in order to contact the contributor
Submitted on : Thursday, May 2, 2019 - 4:34:36 PM
Last modification on : Tuesday, June 1, 2021 - 2:08:09 PM



Mauro Gaio, Ludovic Moncla. Geoparsing and geocoding places in a dynamic space context: The case of hiking descriptions. Human Cognitive Processing, John Benjamins Publishing Company, 2019, Human Cognitive Processing, 66, pp.354-386. ⟨10.1075/hcp.66.10gai⟩. ⟨hal-02117833⟩



Record views