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GIS-KG: building a large-scale hierarchical knowledge graph for geographic information science / Jiaxin Du in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 873 - 897 Titre : GIS-KG: building a large-scale hierarchical knowledge graph for geographic information science Type de document : Article/Communication Auteurs : Jiaxin Du, Auteur ; Shaohua Wang, Auteur ; Xinyue Ye, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 873 - 897 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] apprentissage profond [Termes IGN] approche hiérarchique [Termes IGN] exploration de données [Termes IGN] ingénierie des connaissances [Termes IGN] ontologie [Termes IGN] recherche d'information géographique [Termes IGN] réseau sémantique [Termes IGN] traitement du langage naturel Résumé : (auteur) An organized knowledge base can facilitate the exploration of existing knowledge and the detection of emerging topics in a domain. Knowledge about and around Geographic Information Science and its associated system technologies (GIS) is complex, extensive and emerging rapidly. Taking the challenge, we built a GIS knowledge graph (GIS-KG) by (1) merging existing GIS bodies of knowledge to create a hierarchical ontology and then (2) applying deep-learning methods to map GIS publications to the ontology. We conducted several experiments on information retrieval to evaluate the novelty and effectiveness of the GIS-KG. Results showed the robust support of GIS-KG for knowledge search of existing GIS topics and potential to explore emerging research themes. Numéro de notice : A2022-341 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2005795 Date de publication en ligne : 26/11/2021 En ligne : https://doi.org/10.1080/13658816.2021.2005795 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100515 [article]

Building a collaborative online catalogue of geoportals in Brazil / Eduardo Silverio da Silva in Boletim de Ciências Geodésicas, vol 27 n° 4 ([01/12/2021])  

Public [article]  inBoletim de Ciências Geodésicas > vol 27 n° 4 [01/12/2021] . - 16 p. Titre : Building a collaborative online catalogue of geoportals in Brazil Type de document : Article/Communication Auteurs : Eduardo Silverio da Silva, Auteur ; Silvana Philippi Camboim, Auteur Année de publication : 2021 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] Brésil [Termes IGN] catalogue de données localisées [Termes IGN] géoportail [Termes IGN] infrastructure nationale des données localisées [Termes IGN] recherche d'information géographique [Termes IGN] WebSIG Résumé : (auteur) It is currently possible to account for several institutions with geographic data shared through the INDE portal, with more than half of it being from federal jurisdiction. However, there are subnational geoportals not integrated with this infrastructure, which is difficult to quantify. Therefore, the research problem of this study is finding the state of subnational geographic viewers’ availability, with the general objective of producing a Brazilian panorama and to identify factors that facilitate this availability. A research methodology based on different sources was applied in 27 states and 999 municipalities. As a result, we identified 17 regional, 82 state, and 274 municipal geoportals, with the highest concentration in the South and Southeast regions and lowest in the Northern region. In order to find factors related to geoportals availability, twenty characteristics of each municipality were collected, and Pearson coefficients were calculated, revealing significant correlations for population, economic and tax factors, and non-significant correlations for location factors. This acquired information is essential for the community and must be kept up to date. For this, an online collaborative map based on free software was created, allowing access without registration for data visualization and the registration of users for sending updates to the map. Numéro de notice : A2021-960 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1590/s1982-21702021000400026 Date de publication en ligne : 17/12/2021 En ligne : https://doi.org/10.1590/s1982-21702021000400026 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100072 [article]

Spatial dataset search: Building a dedicated knowledge graph / Mehdi Zhral (2021)  

Public Titre : Spatial dataset search: Building a dedicated knowledge graph Type de document : Article/Communication Auteurs : Mehdi Zhral , Auteur ; Bénédicte Bucher , Auteur ; Marie-Dominique Van Damme , Auteur ; Fayçal Hamdi , Auteur Editeur : AGILE Alliance Année de publication : 2021 Projets : 1-Pas de projet / Conférence : AGILE 2021, 24th AGILE Conference on Geographic Information Science 19/07/2021 22/07/2021 Aurora - Colorado Etats-Unis OA Proceedings Importance : 5 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] découverte de connaissances [Termes IGN] données massives [Termes IGN] données ouvertes [Termes IGN] graphe [Termes IGN] INSPIRE [Termes IGN] jeu de données localisées [Termes IGN] précision sémantique [Termes IGN] recherche d'information géographique [Termes IGN] requête spatiale [Termes IGN] réseau sémantique [Termes IGN] ressources web [Termes IGN] service web géographique [Termes IGN] terminologie [Termes IGN] web des données [Termes IGN] web sémantique géolocalisé Résumé : (auteur) A growing number of spatial datasets are published every year. These can usually be found in dedicated web portals with different structures and specificities. However, finding the dataset that fits user needs is a real challenge as prior knowledge of these portals is needed to retrieve it efficiently. In this article, we present the problem of spatial dataset search and how the use of a geographic Knowledge Graph could improve it. A proposed direction for future work, ex-tending these contributions, is then presented. Numéro de notice : C2021-008 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : https://agile-giss.copernicus.org/articles/2/43/2021/agile-giss-2-43-2021.pdf Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/agile-giss-2-43-2021 En ligne : https://doi.org/10.5194/agile-giss-2-43-2021 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97855

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 OA 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

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements / Yingjie Hu in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 3-4 (March - April 2019) . - pp 714 - 738 Titre : A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements Type de document : Article/Communication Auteurs : Yingjie Hu, Auteur ; Huina Mao, Auteur ; Grant McKenzie, Auteur Année de publication : 2019 Article en page(s) : pp 714 - 738 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie [Termes IGN] analyse de groupement [Termes IGN] information sémantique [Termes IGN] publicité [Termes IGN] recherche d'information géographique [Termes IGN] reconnaissance de noms [Termes IGN] répertoire toponymique [Termes IGN] toponymie locale [Termes IGN] traitement du langage naturel Résumé : (Auteur) Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework. Numéro de notice : A2019-213 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1458986 Date de publication en ligne : 13/04/2018 En ligne : https://doi.org/10.1080/13658816.2018.1458986 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92685 [article]

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