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Reference data enhancement for geographic information retrieval using linked data / Tiago H. V. M. Moura in Transactions in GIS, vol 21 n° 4 (August 2017)
[article]
Titre : Reference data enhancement for geographic information retrieval using linked data Type de document : Article/Communication Auteurs : Tiago H. V. M. Moura, Auteur ; Clodoveu A. Davis Jr., Auteur ; Frederico T. Fonseca, Auteur Année de publication : 2017 Article en page(s) : pp 683 - 700 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] base de connaissances
[Termes IGN] recherche d'information géographique
[Termes IGN] relation sémantique
[Termes IGN] répertoire toponymique
[Termes IGN] service web
[Termes IGN] web des donnéesRésumé : (Auteur) Gazetteers are instrumental in recognizing place names in documents such as Web pages, news, and social media messages. However, creating and maintaining gazetteers is still a complex task. Even though some online gazetteers provide rich sets of geographic names in planetary scale (e.g. GeoNames), other sources must be used to recognize references to urban locations, such as street names, neighborhood names or landmarks. We propose integrating Linked Data sources to create a gazetteer that combines a broad coverage of places with urban detail, including content on geographic and semantic relationships involving places, their multiple names and related non-geographic entities. Our final goal is to expand the possibilities for recognizing, disambiguating and filtering references to places in texts for geographic information retrieval (GIR) and related applications. The resulting ontological gazetteer, named LoG (Linked OntoGazetteer), is accessible through Web services by applications and research initiatives on GIR, text processing, named entity recognition and others. The gazetteer currently contains over 13 million places, 140 million attributes and relationships, and 4.5 million non-geographic entities. Data sources include GeoNames, Freebase, DBPedia and LinkedGeoData, which is based on OpenStreetMap data. An analysis on how these datasets overlap and complement one another is also presented. Numéro de notice : A2017-628 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12238 En ligne : http://dx.doi.org/10.1111/tgis.12238 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86943
in Transactions in GIS > vol 21 n° 4 (August 2017) . - pp 683 - 700[article]Aggregation-based information retrieval system for geospatial data catalogs / Javier Lacasta in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
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Titre : Aggregation-based information retrieval system for geospatial data catalogs Type de document : Article/Communication Auteurs : Javier Lacasta, Auteur ; Javier Lopez-Pellicer, Auteur ; Borja Espejo-García, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 1583 - 1605 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] accès aux données
[Termes IGN] catalogue de données localisées
[Termes IGN] Espagne
[Termes IGN] exploration de données géographiques
[Termes IGN] infrastructure régionale de données localisées
[Termes IGN] métadonnées
[Termes IGN] métadonnées géographiques
[Termes IGN] recherche d'information géographique
[Termes IGN] requête (informatique)
[Termes IGN] service web géographiqueRésumé : (Auteur) Geospatial data catalogs enable users to discover and access geographical information. Prevailing solutions are document oriented and fragment the spatial continuum of the geospatial data into independent and disconnected resources described through metadata. Due to this, the complete answer for a query may be scattered across multiple resources, making its discovery and access more difficult. This paper proposes an improved information retrieval process for geospatial data catalogs that aggregates the search results by identifying the implicit spatial/thematic relations between the metadata records of the resources. These aggregations are constructed in such a way that they match better the user query than each resource individually. Numéro de notice : A2017-313 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1319949 En ligne : http://dx.doi.org/10.1080/13658816.2017.1319949 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85367
in International journal of geographical information science IJGIS > vol 31 n° 7-8 (July - August 2017) . - pp 1583 - 1605[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 079-2017042 RAB Revue Centre de documentation En réserve L003 Disponible Classifying natural-language spatial relation terms with random forest algorithm / Shihong Du in International journal of geographical information science IJGIS, vol 31 n° 3-4 (March-April 2017)
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Titre : Classifying natural-language spatial relation terms with random forest algorithm Type de document : Article/Communication Auteurs : Shihong Du, Auteur ; Xiaonan Wang, Auteur ; Chen-Chieh Feng, Auteur ; Xiuyuan Zhang, Auteur Année de publication : 2017 Article en page(s) : pp 542 - 568 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] apprentissage dirigé
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] intelligence artificielle
[Termes IGN] interface en langage naturel
[Termes IGN] langage naturel (informatique)
[Termes IGN] méthode robuste
[Termes IGN] recherche d'information géographique
[Termes IGN] relation spatiale
[Termes IGN] relation topologique
[Termes IGN] similitude sémantiqueRésumé : (Auteur) The exponential growth of natural language text data in social media has contributed a rich data source for geographic information. However, incorporating such data source for GIS analysis faces tremendous challenges as existing GIS data tend to be geometry based while natural language text data tend to rely on natural language spatial relation (NLSR) terms. To alleviate this problem, one critical step is to translate geometric configurations into NLSR terms, but existing methods to date (e.g. mean value or decision tree algorithm) are insufficient to obtain a precise translation. This study addresses this issue by adopting the random forest (RF) algorithm to automatically learn a robust mapping model from a large number of samples and to evaluate the importance of each variable for each NLSR term. Because the semantic similarity of the collected terms reduces the classification accuracy, different grouping schemes of NLSR terms are used, with their influences on classification results being evaluated. The experiment results demonstrate that the learned model can accurately transform geometric configurations into NLSR terms, and that recognizing different groups of terms require different sets of variables. More importantly, the results of variable importance evaluation indicate that the importance of topology types determined by the 9-intersection model is weaker than metric variables in defining NLSR terms, which contrasts to the assertion of ‘topology matters, metric refines’ in existing studies. Numéro de notice : A2017-078 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1212356 En ligne : http://dx.doi.org/10.1080/13658816.2016.1212356 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84340
in International journal of geographical information science IJGIS > vol 31 n° 3-4 (March-April 2017) . - pp 542 - 568[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-2017021 RAB Revue Centre de documentation En réserve L003 Disponible 079-2017022 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Cross-domain image localization by adaptive feature fusion Type de document : Article/Communication Auteurs : Neelanjan Bhowmik , Auteur ; Li Weng , Auteur ; Valérie Gouet-Brunet , Auteur ; Bahman Soheilian , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2017 Projets : POEME / Da Silva, Jean-Claude Conférence : JURSE 2017, Joint urban remote sensing event 06/03/2017 08/03/2017 Lausanne Suisse Proceedings IEEE Importance : 4 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] appariement d'images
[Termes IGN] environnement de développement
[Termes IGN] estimation de pose
[Termes IGN] géopositionnement
[Termes IGN] modèle de régression
[Termes IGN] recherche d'image basée sur le contenu
[Termes IGN] recherche d'information géographique
[Termes IGN] similitudeRésumé : (auteur) We address the problem of cross-domain image localization, i.e., the ability of estimating the pose of a landmark from visual content acquired under various conditions, such as old photographs, paintings, photos taken at a particular season, etc. We explore a 2D approach where the pose is estimated from geo-localized reference images that visually match the query image. This work focuses on the retrieval of similar images, which is a challenging task for images across different domains. We propose a Content-Based Image Retrieval (CBIR) framework that adaptively combines multiple image descriptions. A regression model is used to select the best feature combinations according to their spatial complementarity, globally for a whole dataset as well as adaptively for each given image. The framework is evaluated on different datasets and the experiments prove its advantage over classical retrieval approaches. Numéro de notice : C2017-028 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/JURSE.2017.7924572 Date de publication en ligne : 11/05/2017 En ligne : https://doi.org/10.1109/JURSE.2017.7924572 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89292 Classified and clustered data constellation: An efficient approach of 3D urban data management / Suhaibah Azri in ISPRS Journal of photogrammetry and remote sensing, vol 113 (March 2016)
[article]
Titre : Classified and clustered data constellation: An efficient approach of 3D urban data management Type de document : Article/Communication Auteurs : Suhaibah Azri, Auteur ; Uznir Ujang, Auteur ; Francesc Antón Castro, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 30 - 42 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse de groupement
[Termes IGN] base de données
[Termes IGN] classification dirigée
[Termes IGN] données massives
[Termes IGN] exploration de données
[Termes IGN] gestion urbaine
[Termes IGN] milieu urbain
[Termes IGN] noeud
[Termes IGN] recherche d'information géographiqueRésumé : (auteur) The growth of urban areas has resulted in massive urban datasets and difficulties handling and managing issues related to urban areas. Huge and massive datasets can degrade data retrieval and information analysis performance. In addition, the urban environment is very difficult to manage because it involves various types of data, such as multiple types of zoning themes in the case of urban mixed-use development. Thus, a special technique for efficient handling and management of urban data is necessary. This paper proposes a structure called Classified and Clustered Data Constellation (CCDC) for urban data management. CCDC operates on the basis of two filters: classification and clustering. To boost up the performance of information retrieval, CCDC offers a minimal percentage of overlap among nodes and coverage area to avoid repetitive data entry and multipath query. The results of tests conducted on several urban mixed-use development datasets using CCDC verify that it efficiently retrieves their semantic and spatial information. Further, comparisons conducted between CCDC and existing clustering and data constellation techniques, from the aspect of preservation of minimal overlap and coverage, confirm that the proposed structure is capable of preserving the minimum overlap and coverage area among nodes. Our overall results indicate that CCDC is efficient in handling and managing urban data, especially urban mixed-use development applications. Numéro de notice : A2016-531 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.12.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.12.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81614
in ISPRS Journal of photogrammetry and remote sensing > vol 113 (March 2016) . - pp 30 - 42[article]European handbook of crowdsourced geographic information, ch. 14. Querying VGI by semantic enrichment / Robert Lemmens (2016)PermalinkGeographic ontologies, gazetteers and multilingualism / Robert Laurini in Future internet, vol 7 n° 1 (March 2015)PermalinkProceedings of the 9th Workshop on Geographic Information Retrieval, GIR'2015 / Ross S. Purves (2015)PermalinkPermalinkLinking time geography and activity theory to support the activities of mobile information seekers / Paul Crease in Transactions in GIS, vol 17 n° 4 (August 2013)PermalinkEvolutionary search for understanding movement dynamics on mixed networks / William M. Spears in Geoinformatica, vol 17 n° 2 (April 2013)PermalinkDiscovery and integration of Web 2.0 content into Geospatial Information Infrastructures : a use case in wild fire monitoring / M. Nunez-Redo (22/08/2011)PermalinkExploiting geographic references of documents in a geographical information retrieval system using an ontology-based index / N. Brisaboa in Geoinformatica, vol 14 n° 3 (July 2010)PermalinkNormalizing spatial information to improve geographical information indexing and retrieval in digital libraries / D. Palacio (26/05/2010)PermalinkUtilisation de sites Web, (Wikipedia, Flickr, Google) pour caractériser des objets géographiques / Léa Massiot (2010)Permalink