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A graph-based approach for representing addresses in geocoding / Chen Zhang in Computers, Environment and Urban Systems, vol 100 (March 2023)  

Public [article]  inComputers, Environment and Urban Systems > vol 100 (March 2023) . - n° 101937 Titre : A graph-based approach for representing addresses in geocoding Type de document : Article/Communication Auteurs : Chen Zhang, Auteur ; Biao He, Auteur ; Renzhong Guo, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101937 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] appariement d'adresses [Termes IGN] base de données d'adresses [Termes IGN] géocodage par adresse postale [Termes IGN] graphe [Termes IGN] stockage de données [Termes IGN] toponyme Résumé : (auteur) Addresses, one of the most important geographical reference systems in natural languages, are usually used to search spatial objects in daily life. Geocoding concatenates text with georeferenced coordinates and is an essential middleware service in geographic information applications. Despite its importance, geocoding remains challenging with only text as input, hindering text matching in reference databases without the specific text. To optimize the storage and retrieval of addresses in databases, this work proposes a graph-based approach for representing addresses. The approach clarifies the characteristics of relative concepts, designs a graph structure and identifies modelling strategies. Furthermore, a schema is proposed to perform address matching and toponym disambiguation using an address graph. The model is implemented on a graph database, and experimental tasks are employed to demonstrate its effectiveness. The approach provides a new reference for developers when creating address databases. Numéro de notice : A2023-126 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101937 Date de publication en ligne : 04/01/2023 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101937 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102505 [article]

Automatic identification of addresses: A systematic literature review / Paula Cruz in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 1 (January 2022) . - n° 11 Titre : Automatic identification of addresses: A systematic literature review Type de document : Article/Communication Auteurs : Paula Cruz, Auteur ; Leonardo Vanneschi, Auteur ; Marco Painho, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 11 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] appariement d'adresses [Termes IGN] apprentissage automatique [Termes IGN] apprentissage profond [Termes IGN] base de données d'adresses [Termes IGN] géocodage par adresse postale [Termes IGN] Geoparsing [Termes IGN] service fondé sur la position Résumé : (auteur) Address matching continues to play a central role at various levels, through geocoding and data integration from different sources, with a view to promote activities such as urban planning, location-based services, and the construction of databases like those used in census operations. However, the task of address matching continues to face several challenges, such as non-standard or incomplete address records or addresses written in more complex languages. In order to better understand how current limitations can be overcome, this paper conducted a systematic literature review focused on automated approaches to address matching and their evolution across time. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, resulting in a final set of 41 papers published between 2002 and 2021, the great majority of which are after 2017, with Chinese authors leading the way. The main findings revealed a consistent move from more traditional approaches to deep learning methods based on semantics, encoder-decoder architectures, and attention mechanisms, as well as the very recent adoption of hybrid approaches making an increased use of spatial constraints and entities. The adoption of evolutionary-based approaches and privacy preserving methods stand as some of the research gaps to address in future studies. Numéro de notice : A2022-088 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi11010011 Date de publication en ligne : 29/12/2021 En ligne : https://doi.org/10.3390/ijgi11010011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99497 [article]

Investigating the quality of reverse geocoding services using text similarity techniques and logistic regression analysis / Batuhan Kilic in Cartography and Geographic Information Science, Vol 47 n° 4 (July 2020)  

Public [article]  inCartography and Geographic Information Science > Vol 47 n° 4 (July 2020) . - pp 336 - 349 Titre : Investigating the quality of reverse geocoding services using text similarity techniques and logistic regression analysis Type de document : Article/Communication Auteurs : Batuhan Kilic, Auteur ; Fatih Gülgen, Auteur Année de publication : 2020 Article en page(s) : pp 336 - 349 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] exploration de texte [Termes IGN] géocodage inverse [Termes IGN] géocodage par adresse postale [Termes IGN] logique binaire [Termes IGN] qualité des données [Termes IGN] régression [Termes IGN] similitude sémantique Résumé : (auteur) Location, usually defined by postal address information or geographic coordinate values, is one of the leading themes in geography. Famous global mapping services such as ArcGIS Online, Bing Maps, Google Maps, or Yandex Maps can provide users with address information of any geographic coordinates using reverse geocoding. The accuracy of retrieved addresses is quite essential for a service user. Several researchers have evaluated the accuracy of the process based on the positional errors between the retrieved and actual addresses. This article proposes a different assessment based on text similarity algorithms. In this study, the authors examine the outcomes of 15 different text similarity algorithms by comparing them with the reference data. They benefit from the binary logistic regression to evaluate the results. At the end of the case study, they conclude that the soft-term frequency/inverse document frequency algorithm is the most appropriate to measure the quality of postal addresses of all tested services. The Jaccard algorithm also produces successful results only for Google and Bing Maps services. Moreover, the study allows the reader to assess the results of reverse geocoding derived from the global map platforms that serve in the test region. Numéro de notice : A2020-339 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1746198 Date de publication en ligne : 20/04/2020 En ligne : https://doi.org/10.1080/15230406.2020.1746198 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95214 [article]

Exemplaires(1)

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032-2020041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

How much do we learn from addresses? On the syntax, semantics and pragmatics of addressing systems / Ali Javidaneh in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - 27 p. Titre : How much do we learn from addresses? On the syntax, semantics and pragmatics of addressing systems Type de document : Article/Communication Auteurs : Ali Javidaneh, Auteur ; Farid Karimipour, Auteur ; Negar Alinaghi, Auteur Année de publication : 2020 Article en page(s) : 27 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] adresse postale [Termes IGN] appariement d'adresses [Termes IGN] cognition [Termes IGN] géocodage par adresse postale [Termes IGN] modèle orienté agent [Termes IGN] représentation mentale spatiale [Termes IGN] segmentation sémantique [Termes IGN] structure syntaxique Résumé : (auteur) An address is a specification that refers to a unique location on Earth. While there has been a considerable amount of research on the syntactic structure of addressing systems in order to evaluate and improve their quality, aspects of semantics and pragmatics have been less explored. An address is primarily associated by humans to the elements of their spatial mental representations, but may also influence their spatial knowledge and activities through the level of detail it provides. Therefore, it is not only important how addressing components are structured, but it is also of interest to study their meaning as well as the pragmatics in relation to an interpreting agent. This article studies three forms of addresses (i.e., structured as in Austria, semi-formal as in Japan, and descriptive as in Iran) under the principles of semiotics (i.e., through levels of syntax, semantics, and pragmatics). Syntax is discussed through formal definitions of the addressing systems, while semantics and pragmatics are assessed through an agent-based model to explore how they influence spatial knowledge acquisition and growth. Numéro de notice : A2020-302 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050317 Date de publication en ligne : 11/05/2020 En ligne : https://doi.org/10.3390/ijgi9050317 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95142 [article]

Geocoding of trees from street addresses and street-level images / Daniel Laumer in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 162 (April 2020) . - pp 125 - 136 Titre : Geocoding of trees from street addresses and street-level images Type de document : Article/Communication Auteurs : Daniel Laumer, Auteur ; Nico Lang, Auteur ; Natalie Van Doorn, Auteur Année de publication : 2020 Article en page(s) : pp 125 - 136 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse des correspondances [Termes IGN] apprentissage profond [Termes IGN] arbre urbain [Termes IGN] Californie (Etats-Unis) [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'arbres [Termes IGN] détection d'objet [Termes IGN] géocodage par adresse postale [Termes IGN] image panoramique [Termes IGN] image Streetview [Termes IGN] inventaire [Termes IGN] service écosystémique [Termes IGN] zone urbaine Résumé : (auteur) We introduce an approach for updating older tree inventories with geographic coordinates using street-level panorama images and a global optimization framework for tree instance matching. Geolocations of trees in inventories until the early 2000s where recorded using street addresses whereas newer inventories use GPS. Our method retrofits older inventories with geographic coordinates to allow connecting them with newer inventories to facilitate long-term studies on tree mortality etc. What makes this problem challenging is the different number of trees per street address, the heterogeneous appearance of different tree instances in the images, ambiguous tree positions if viewed from multiple images and occlusions. To solve this assignment problem, we (i) detect trees in Google street-view panoramas using deep learning, (ii) combine multi-view detections per tree into a single representation, (iii) and match detected trees with given trees per street address with a global optimization approach. Experiments for trees in 5 cities in California, USA, show that we are able to assign geographic coordinates to 38% of the street trees, which is a good starting point for long-term studies on the ecosystem services value of street trees at large scale. Numéro de notice : A2020-124 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.001 Date de publication en ligne : 21/02/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.001 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94749 [article]

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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Historical collaborative geocoding / Rémi Cura in ISPRS International journal of geo-information, vol 7 n° 7 (July 2018)    

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La cartographie et la géomatique au service de la santé pour la région Ile-de-France / Carlos Garcia (2013)

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La géomatique au service de la santé / Anthony Necha (2012)

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Influence of street reference data on geocoding quality / P. Zandbergen in Geocarto international, vol 26 n° 1 (February 2011)  

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Cartographier les pratiques et les usages des parisiens / J.L. Pinol in Le monde des cartes, n° 204 (juin 2010)

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Accompagner au développement d'un logiciel géodécisionnel / Gildas Mfoumbi (2010)

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Assessing the certainty of locations produced by an address geocoding system / C.A. Davis in Geoinformatica, vol 11 n° 1 (March - May 2007)  

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Evaluating the uncertainty caused by Post Office Box addresses in environmental health studies: A restricted Monte Carlo approach / X. Shi in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)  

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Mise en place d'un SIG à l'Institut Pasteur de la Guyane pour la surveillance des cas confirmés de dengue en Guyane / Xavier Thauvin (2006)

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