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scientifique

Learning embeddings for cross-time geographic areas represented as graphs / Margarita Khokhlova (2021)  

Public Titre : Learning embeddings for cross-time geographic areas represented as graphs Type de document : Article/Communication Auteurs : Margarita Khokhlova, Auteur ; Nathalie Abadie , Auteur ; Valérie Gouet-Brunet , Auteur ; Liming Chen, Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2021 Projets : Alegoria / Gouet-Brunet, Valérie Conférence : SAC 2021, 36th Annual ACM Symposium on Applied Computing 22/03/2021 26/03/2021 en ligne Proceedings ACM Importance : pp 559 - 568 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] arête [Termes IGN] classification par réseau neuronal [Termes IGN] entité géographique [Termes IGN] graphe flou [Termes IGN] image aérienne à axe vertical [Termes IGN] noeud [Termes IGN] relation spatiale [Termes IGN] représentation graphique [Termes IGN] réseau neuronal de graphes Résumé : (auteur) Geographic entities from the vertical aerial images can be viewed as discrete objects and represented as nodes in a graph, linked to each other by edges capturing their spatial relationships. Over time, the natural and man made landscape may evolve and thus also their graph representations. This paper addresses the challenging problem of the retrieval and fuzzy matching of graphs to localize near-identical geographical areas across time. Several use-case scenarios are proposed for the end-to-end learning of a graph embedding using Graph Neural Networks (GNN), along with an effective baseline without learning. The results demonstrate the efficiency of our approach, that enables efficient similarity reasoning for novel hand-engineered cross-time graph data. Code and data processing scripts are available online. Numéro de notice : C2021-002 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1145/3412841.3441936 En ligne : https://doi.org/10.1145/3412841.3441936 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97583

Semantic trajectory segmentation based on change-point detection and ontology / Yuan Gao in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 12 (December 2020) . - pp 2361 - 2394 Titre : Semantic trajectory segmentation based on change-point detection and ontology Type de document : Article/Communication Auteurs : Yuan Gao, Auteur ; Longfei Huang, Auteur ; Jun Feng, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2361 - 2394 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cible mobile [Termes IGN] détection de changement [Termes IGN] information sémantique [Termes IGN] modèle dynamique [Termes IGN] objet mobile [Termes IGN] ontologie [Termes IGN] point d'intérêt [Termes IGN] probabilité [Termes IGN] segmentation sémantique [Termes IGN] trajectoire Résumé : (auteur) Trajectory segmentation is a fundamental issue in GPS trajectory analytics. The task of dividing a raw trajectory into reasonable sub-trajectories and annotating them based on moving subject’s intentions and application domains remains a challenge. This is due to the highly dynamic nature of individuals’ patterns of movement and the complex relationships between such patterns and surrounding points of interest. In this paper, we present a framework called SEMANTIC-SEG for automatic semantic segmentation of trajectories from GPS readings. For the decomposition component of SEMANTIC-SEG, a moving pattern change detection (MPCD) algorithm is proposed to divide the raw trajectory into segments that are homogeneous in their movement conditions. A generic ontology and a spatiotemporal probability model for segmentation are then introduced to implement a bottom-up ontology-based reasoning for semantic enrichment. The experimental results on three real-world datasets show that MPCD can more effectively identify the semantically significant change-points in a pattern of movement than four existing baseline methods. Moreover, experiments are conducted to demonstrate how the proposed SEMANTIC-SEG framework can be applied. Numéro de notice : A2020-689 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1798966 date de publication en ligne : 04/08/2020 En ligne : https://doi.org/10.1080/13658816.2020.1798966 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96226 [article]

A semantic graph database for the interoperability of 3D GIS data / Eva Savina Malinverni in Applied geomatics, vol 12 n° 3 (September 2020)  

Public [article]  inApplied geomatics > vol 12 n° 3 (September 2020) . - 14 p. Titre : A semantic graph database for the interoperability of 3D GIS data Type de document : Article/Communication Auteurs : Eva Savina Malinverni, Auteur ; Berardo Naticchia, Auteur ; Jose Luis Lerma Garcia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] base de données [Termes IGN] bâtiment [Termes IGN] CityGML [Termes IGN] conservation de documents [Termes IGN] données hétérogènes [Termes IGN] graphe [Termes IGN] indoorGML [Termes IGN] interopérabilité sémantique [Termes IGN] modélisation 3D [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] ontologie [Termes IGN] partage de données localisées [Termes IGN] restauration de document [Termes IGN] SIG 3D [Termes IGN] stockage de données [Termes IGN] web sémantique Résumé : (auteur) In the last decades, the use of information management systems in the building data processing led to radical changes to the methods of data production, documentation and archiving. In particular, the possibilities, given by these information systems, to visualize the 3D model and to formulate queries have placed the question of the information sharing in digital format. The integration of information systems represents an efficient solution for defining smart, sustainable and resilient projects, such as conservation and restoration processes, giving the possibilities to combine heterogeneous data. GIS provides a robust data storage system, a definition of topological and semantic relationships and spatial queries. 3D GIS makes possible the creation of three-dimensional model in a geospatial context. To promote the interoperability of GIS data, the present research aims first to analyse methods of conversion in CityGML and IndoorGML model, defining an ontological domain. This has led to the creation of a new enriched model, based on connections among the different elements of the urban model in GIS environment, and to the possibility to formulate queries based on these relations. The second step consists in collecting all data translated into a specific format that fill a graph database in a semantic web environment, while maintaining those relationships. The semantic web technology represents an efficient tool of interoperability that leaves open the possibility to import BIM data in the same graph database and to join both GIS and BIM models. The outcome will offer substantial benefits during the entire project life cycle. This methodology can also be applied to cultural heritage where the information management plays a key role. Numéro de notice : A2020-561 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-020-00334-3 date de publication en ligne : 24/08/2020 En ligne : https://doi.org/10.1007/s12518-020-00334-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95875 [article]

Conciliating perspectives from mapping agencies and web of data on successful European SDIs: toward a European geographic knowledge graph / Bénédicte Bucher in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 2 (February 2020) . - 23 p. Titre : Conciliating perspectives from mapping agencies and web of data on successful European SDIs: toward a European geographic knowledge graph Type de document : Article/Communication Auteurs : Bénédicte Bucher , Auteur ; Esa Tiainen, Auteur ; Thomas Ellett von Brasch, Auteur ; Paul Janssen, Auteur ; Dimitris Kotzinos, Auteur ; Marjan Ceh, Auteur ; Martijn Rijsdijk, Auteur ; Marie-Dominique Van Damme , Auteur ; Mehdi Zhral , Auteur Année de publication : 2020 Projets : URCLIM / Masson, Valéry Article en page(s) : 23 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] cartographe [Termes IGN] données ouvertes [Termes IGN] graphique [Termes IGN] harmonisation des données [Termes IGN] hétérogénéité sémantique [Termes IGN] infrastructure européenne de données localisées [Termes IGN] INSPIRE [Termes IGN] ontologie [Termes IGN] organisme cartographique national [Termes IGN] Web des données [Termes IGN] web sémantique Résumé : (auteur) Spatial Data Infrastructures (SDIs) are a key asset for Europe. This paper concentrates on unsolved issues in SDIs in Europe related to the management of semantic heterogeneities. It studies contributions and competences from two communities in this field: cartographers, authoritative data providers, and geographic information scientists on the one hand, and computer scientists working on the Web of Data on the other. During several workshops organized by the EuroSDR and Eurogeographics organizations, the authors analyzed their complementarity and discovered reasons for the difficult collaboration between these communities. They have different and sometimes conflicting perspectives on what successful SDIs should look like, as well as on priorities. We developed a proposal to integrate both perspectives, which is centered on the elaboration of an open European Geographical Knowledge Graph. Its structure reuses results from the literature on geographical information ontologies. It is associated with a multifaceted roadmap addressing interrelated aspects of SDIs. Numéro de notice : A2020-054 Affiliation des auteurs : LaSTIG+Ext (2016-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9020062 date de publication en ligne : 21/01/2020 En ligne : https://doi.org/10.3390/ijgi9020062 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94537 [article]

Comparing supervised learning algorithms for Spatial Nominal Entity recognition / Amine Medad (2020)  

Public Titre : Comparing supervised learning algorithms for Spatial Nominal Entity recognition Type de document : Article/Communication Auteurs : Amine Medad, Auteur ; Mauro Gaio, Auteur ; Ludovic Moncla, Auteur ; Sébastien Mustière , Auteur ; Yannick Le Nir, Auteur Editeur : Göttingen : Copernicus publications Année de publication : 2020 Collection : AGILE GIScience Series num. vol 1 Projets : 1-Pas de projet / Conférence : AGILE 2020, 23rd AGILE Conference on Geographic Information Science 16/06/2020 19/06/2020 Chania - Crète Grèce Open Access Proceedings Importance : 18 p. Format : 21 x 30 cm Note générale : biblographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] algorithme d'apprentissage [Termes IGN] analyse comparative [Termes IGN] entité géographique [Termes IGN] recherche d'information géographique [Termes IGN] reconnaissance de noms [Termes IGN] traitement du langage naturel Résumé : (auteur) Discourse may contain both named and nominal entities. Most common nouns or nominal mentions in natural language do not have a single, simple meaning but rather a number of related meanings. This form of ambiguity led to the development of a task in natural language processing known as Word Sense Disambiguation. Recognition and categorisation of named and nominal entities is an essential step for Word Sense Disambiguation methods. Up to now, named entity recognition and categorisation systems mainly focused on the annotation, categorisation and identification of named entities. This paper focuses on the annotation and the identification of spatial nominal entities. We explore the combination of Transfer Learning principle and supervised learning algorithms, in order to build a system to detect spatial nominal entities. For this purpose, different supervised learning algorithms are evaluated with three different context sizes on two manually annotated datasets built from Wikipedia articles and hiking description texts. The studied algorithms have been selected for one or more of their specific properties potentially useful in solving our problem. The results of the first phase of experiments reveal that the selected algorithms have similar performances in terms of ability to detect spatial nominal entities. The study also confirms the importance of the size of the window to describe the context, when word-embedding principle is used to represent the semantics of each word. Numéro de notice : C2020-013 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/agile-giss-1-15-2020 date de publication en ligne : 15/07/2020 En ligne : https://doi.org/10.5194/agile-giss-1-15-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95688

MapGenOnto: A shared ontology for map generalisation and multi-scale visualisation / Guillaume Touya (2020)  

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Des empreintes cartographiques : restitution de données géohistoriques à partir de la Carte de France de Cassini, 1750-1789 / Bertrand Duménieu in Cartes & Géomatique, n° 241-242 (décembre 2019)

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Place and sentiment-based life story analysis: From the Spanish republican army to the French resistance / Catherine Dominguès in Revue française des sciences de l'information et de la communication, vol 17 (2019)  

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Computing and querying strict, approximate, and metrically refined topological relations in linked geographic data / Blake Regalia in Transactions in GIS, vol 23 n° 3 (June 2019)  

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Deeply integrating linked data with geographic information systems / Gengchen Mai in Transactions in GIS, vol 23 n° 3 (June 2019)  

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Data linking by indirect spatial referencing systems, [report of] EuroSDR - EuroGeographics seminar, September 5th - 6th, 2018 - Paris, France / Bénédicte Bucher (2019)  

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Numérique et territoires / Philippe Cohard (2019)

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Spatial decision support in urban environments using machine learning, 3D geo-visualization and semantic integration of multi-source data / Nikolaos Sideris (2019)  

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Thinking Time Geography / Kajsa Ellegård (2019)  

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The world, the computer, and the mind : how Andrew Frank helped make human language and cognition cornerstones of geographic information science / Daniel R. Montello in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)  

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