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Spatially oriented convolutional neural network for spatial relation extraction from natural language texts / Qinjun Qiu in Transactions in GIS, vol 26 n° 2 (April 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 2 (April 2022) . - pp 839 - 866 Titre : Spatially oriented convolutional neural network for spatial relation extraction from natural language texts Type de document : Article/Communication Auteurs : Qinjun Qiu, Auteur ; Zhong Xie, Auteur ; Kai Ma, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 839 - 866 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] appariement sémantique [Termes IGN] apprentissage dirigé [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] exploration de données [Termes IGN] langage naturel (informatique) [Termes IGN] proximité sémantique [Termes IGN] relation spatiale [Termes IGN] relation topologique [Termes IGN] site wiki [Termes IGN] spatial metrics [Termes IGN] système à base de connaissances Résumé : (auteur) Spatial relation extraction (e.g., topological relations, directional relations, and distance relations) from natural language descriptions is a fundamental but challenging task in several practical applications. Current state-of-the-art methods rely on rule-based metrics, either those specifically developed for extracting spatial relations or those integrated in methods that combine multiple metrics. However, these methods all rely on developed rules and do not effectively capture the characteristics of natural language spatial relations because the descriptions may be heterogeneous and vague and may be context sparse. In this article, we present a spatially oriented piecewise convolutional neural network (SP-CNN) that is specifically designed with these linguistic issues in mind. Our method extends a general piecewise convolutional neural network with a set of improvements designed to tackle the task of spatial relation extraction. We also propose an automated workflow for generating training datasets by integrating new sentences with those in a knowledge base, based on string similarity and semantic similarity, and then transforming the sentences into training data. We exploit a spatially oriented channel that uses prior human knowledge to automatically match words and understand the linguistic clues to spatial relations, finally leading to an extraction decision. We present both the qualitative and quantitative performance of the proposed methodology using a large dataset collected from Wikipedia. The experimental results demonstrate that the SP-CNN, with its supervised machine learning, can significantly outperform current state-of-the-art methods on constructed datasets. Numéro de notice : A2022-365 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12887 Date de publication en ligne : 27/12/2021 En ligne : https://doi.org/10.1111/tgis.12887 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100584 [article]

Connecting family trees to construct a population-scale and longitudinal geo-social network for the U.S. / Caglar Koylu in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 12 (December 2021) . - pp 2380 - 2423 Titre : Connecting family trees to construct a population-scale and longitudinal geo-social network for the U.S. Type de document : Article/Communication Auteurs : Caglar Koylu, Auteur ; Diansheng Guo, Auteur ; Yuan Huang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2380 - 2423 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] appariement sémantique [Termes IGN] collecte de données [Termes IGN] démographie [Termes IGN] dix-neuvième siècle [Termes IGN] données localisées des bénévoles [Termes IGN] données publiques [Termes IGN] Etats-Unis [Termes IGN] généalogie [Termes IGN] géocodage [Termes IGN] historique des données [Termes IGN] itération [Termes IGN] migration humaine [Termes IGN] mobilité [Termes IGN] réseau social géodépendant [Termes IGN] système d'information historique Résumé : (auteur) We collected 92,832 user-contributed and publicly available family trees from rootsweb.com, including 250 million individuals who were born in North America and Europe between 1630 and 1930. We cleaned and connected the family trees to create a population-scale and longitudinal family tree dataset using a workflow of data collection and cleaning, geocoding, fuzzy record linkage and a relation-based iterative search for connecting trees and deduplication of records. Given the largest connected component of nearly 40 million individuals, and a total of 80 million individuals, we generated, to date, the largest population-scale and longitudinal geo-social network over centuries. We evaluated the representativeness of the family tree dataset for historical population demography and mobility by comparing the data to the 1880 Census. Our results showed that the family trees were biased towards males, the elderly, farmers, and native-born white segments of the population. Individuals were highly mobile – in our 1880 sample of parent-child pairs where both were born in the U.S., 47% were born in different states. Our findings agreed with prior studies that people migrated from East to West in horizontal bands, and the trend was reflected in the dialects and regional structure of the U.S. Numéro de notice : A2021-876 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1821885 Date de publication en ligne : 30/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1821885 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99139 [article]

Semantic signatures for large-scale visual localization / Li Weng in Multimedia tools and applications, vol 80 n° 15 (June 2021)  

Public [article]  inMultimedia tools and applications > vol 80 n° 15 (June 2021) . - pp 22347 - 22372 Titre : Semantic signatures for large-scale visual localization Type de document : Article/Communication Auteurs : Li Weng , Auteur ; Valérie Gouet-Brunet , Auteur ; Bahman Soheilian , Auteur Année de publication : 2021 Projets : THINGS2D0 / Gouet-Brunet, Valérie Article en page(s) : pp 22347 - 22372 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement sémantique [Termes IGN] extraction de traits caractéristiques [Termes IGN] image numérique [Termes IGN] information sémantique [Termes IGN] recherche d'image basée sur le contenu [Termes IGN] segmentation sémantique [Termes IGN] zone urbaine Résumé : (auteur) Visual localization is a useful alternative to standard localization techniques. It works by utilizing cameras. In a typical scenario, features are extracted from captured images and compared with geo-referenced databases. Location information is then inferred from the matching results. Conventional schemes mainly use low-level visual features. These approaches offer good accuracy but suffer from scalability issues. In order to assist localization in large urban areas, this work explores a different path by utilizing high-level semantic information. It is found that object information in a street view can facilitate localization. A novel descriptor scheme called “semantic signature” is proposed to summarize this information. A semantic signature consists of type and angle information of visible objects at a spatial location. Several metrics and protocols are proposed for signature comparison and retrieval. They illustrate different trade-offs between accuracy and complexity. Extensive simulation results confirm the potential of the proposed scheme in large-scale applications. This paper is an extended version of a conference paper in CBMI’18. A more efficient retrieval protocol is presented with additional experiment results. Numéro de notice : A2021-787 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers ArXiv Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11042-020-08992-6 Date de publication en ligne : 07/05/2020 En ligne : https://doi.org/10.1007/s11042-020-08992-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95407 [article]

Stop-and-move sequence expressions over semantic trajectories / Yenier Torres Izquierdo in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 4 (April 2021) . - pp 793 - 818 Titre : Stop-and-move sequence expressions over semantic trajectories Type de document : Article/Communication Auteurs : Yenier Torres Izquierdo, Auteur ; Grettel Monteagudo Garcia, Auteur ; Marco A. Casanova, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 793 - 818 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] appariement sémantique [Termes IGN] exploration de données [Termes IGN] image Flickr [Termes IGN] information sémantique [Termes IGN] intelligence artificielle [Termes IGN] langage de requête [Termes IGN] RDF [Termes IGN] SPARQL Résumé : (auteur) Stop-and-move semantic trajectories are segmented trajectories where the stops and moves are semantically enriched with additional data. A query language for semantic trajectory datasets has to include selectors for stops or moves based on their enrichments and sequence expressions that define how to match the results of selectors with the sequence the semantic trajectory defines. This article addresses the problem of searching semantic trajectories, using stop-and-move sequence expressions. The article first proposes a formal framework to define semantic trajectories and introduces stop-and-move sequence expressions, with well-defined syntax and semantics, which act as an expressive query language for semantic trajectories. Then, it describes a concrete semantic trajectory model in RDF, defines SPARQL stop-and-move sequence expressions and discusses strategies to compile such expressions into SPARQL queries. Lastly, the article specifies user-friendly keyword search expressions over semantic trajectories based on the use of keywords to specify stop-and-move queries, and the adoption of terms with predefined semantics to compose sequence expressions. It then shows how to compile such keyword search expressions into SPARQL queries. Finally, it provides a proof-of-concept experiment over a semantic trajectory dataset constructed with user-generated content from Flickr, combined with Wikipedia data. Numéro de notice : A2021-270 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1793157 Date de publication en ligne : 20/07/2020 En ligne : https://doi.org/10.1080/13658816.2020.1793157 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97328 [article]

Toward a yearly country-scale CORINE land-cover map without using images: A map translation approach / Luc Baudoux in Remote sensing, Vol 13 n° 6 (March 2021)  

Public [article]  inRemote sensing > Vol 13 n° 6 (March 2021) . - n° 1060 - 32 p. Titre : Toward a yearly country-scale CORINE land-cover map without using images: A map translation approach Type de document : Article/Communication Auteurs : Luc Baudoux , Auteur ; Jordi Inglada, Auteur ; Clément Mallet , Auteur Année de publication : 2021 Projets : AI4GEO / Gouet-Brunet, Valérie, MAESTRIA / Mallet, Clément Article en page(s) : n° 1060 - 32 p. Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] appariement sémantique [Termes IGN] apprentissage dirigé [Termes IGN] carte d'occupation du sol [Termes IGN] changement d'occupation du sol [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] Corine Land Cover [Termes IGN] détection de changement [Termes IGN] image à haute résolution [Termes IGN] inférence [Termes IGN] mise à jour automatique [Termes IGN] mise à jour de base de données Résumé : (Auteur) CORINE Land-Cover (CLC) and its by-products are considered as a reference baseline for land-cover mapping over Europe and subsequent applications. CLC is currently tediously produced each six years from both the visual interpretation and the automatic analysis of a large amount of remote sensing images. Observing that various European countries regularly produce in parallel their own land-cover country-scaled maps with their own specifications, we propose to directly infer CORINE Land-Cover from an existing map, therefore steadily decreasing the updating time-frame. No additional remote sensing image is required. In this paper, we focus more specifically on translating a country-scale remote sensed map, OSO (France), into CORINE Land Cover, in a supervised way. OSO and CLC not only differ in nomenclature but also in spatial resolution. We jointly harmonize both dimensions using a contextual and asymmetrical Convolution Neural Network with positional encoding. We show for various use cases that our method achieves a superior performance than the traditional semantic-based translation approach, achieving an 81% accuracy over all of France, close to the targeted 85% accuracy of CLC. Numéro de notice : A2021-244 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13061060 Date de publication en ligne : 11/03/2021 En ligne : https://dx.doi.org/10.3390/rs13061060 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97311 [article]

Enjeux et méthodes d’un liage de référentiels géographiques : l’exemple du projet de recherche ALEGORIA / Clara Lelièvre (2021) 

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A deep learning architecture for semantic address matching / Yue Lin in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)  

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Modelling perceived risks to personal privacy from location disclosure on online social networks / Fatma S. Alrayes in International journal of geographical information science IJGIS, vol 34 n° 1 (January 2020)  

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ATLAS: A three-layered approach to facade parsing / Markus Mathias in International journal of computer vision, vol 118 n° 1 (May 2016)  

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Générer une emprise de carte à partir des toponymes d’un texte / Geoffrey Brun (2013)

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An evaluation of ontology matching in geo-service applications / L. Vaccari in Geoinformatica, vol 16 n° 1 (January 2012)  

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Découverte de services basée sur leurs protocoles de conversation / J.C. Corrales in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 12 n° 1 (janvier - février 2007)

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Plate-forme AFIA, Nice, 30 mai - 3 juin 2005, 1. Journéee thématique Web sémantique pour le e-learning / Rose Dieng-Kuntz (2005)

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Formalisation des spécifications de bases de données géographiques pour une meilleure compréhension des données / Nils Gesbert (2004)

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Généralisation et représentation multiple, ch. 9. Associer des données : l'appariement / Cécile Lemarié (2002)

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