GAIO, Mauro; MONCLA, Ludovic

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GAIO, Mauro
Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour [LIUPPA]

MONCLA, Ludovic
Institut de Recherche de l'Ecole Navale [IRENAV]
Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour [LIUPPA]

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Communication dans un congrès avec actes

Ce document a été publié dans

The Ninth International Conference on Advanced Geographic Information Systems, Applications, and Services (GEOProcessing 2017), 2017-03-19, Nice. 2017-03

Résumé en anglais

The textual geographical information is frequently organized around spatial named entities. Such entities have intrinsic ambiguities and Named Entity Recognition and Classification methods should be improved in order to handle this problem. This article describes a knowledge-based method implementing a full process with the aim of annotating in a more precise way the spatial information in the textual documents. This gain in accuracy guarantees a better analysis of the spatial information and a better disambiguation of places. The backbone of our proposal is a construction grammar and a cascaded finite-state transducers. The evaluation shows that the introduced concept of hierarchical overlapping, is very helpful to detect a local context associated with Named Entities.< Réduire

Mots clés en anglais

Geo-information processing

Geo-spatial Web Ser- vices and processing

Geo-spatial data mining

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Extended Named Entity Recognition Using Finite-State Transducers: An Application To Place Names

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Résumé en anglais

Mots clés en anglais

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