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Fictive motion extraction and classification / Ekaterina Egorova in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)
[article]
Titre : Fictive motion extraction and classification Type de document : Article/Communication Auteurs : Ekaterina Egorova, Auteur ; Ludovic Moncla , Auteur ; Mauro Gaio, Auteur ; Christophe Claramunt, Auteur ; Ross S. Purves, Auteur Année de publication : 2018 Article en page(s) : pp 2247 - 2271 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] Alpes
[Termes IGN] base de règles
[Termes IGN] corpus
[Termes IGN] extraction automatique
[Termes IGN] traitement du langage naturelRésumé : (Auteur) Fictive motion (e.g. ‘The highway runs along the coast’) is a pervasive phenomenon in language that can imply both a static and a moving observer. In a corpus of alpine narratives, it is used in three types of spatial descriptions: conveying the actual motion of the observer, describing a vista and communicating encyclopaedic spatial knowledge. This study takes a knowledge-based approach to develop rules for automated extraction and classification of these types based on an annotated corpus of fictive motion instances. In particular, we identify the differences in the set of concepts involved into the production of the three types of descriptions, followed by their linguistic operationalization. Based on that, we build a set of rules that classify fictive motion with an overall precision of 0.87 and recall of 0.71. The article highlights the importance of examining spatially rich, naturally occurring corpora for the lines of work dealing with the automated interpretation of spatial information in texts, as well as, more broadly, investigation of spatial language involved into various types of spatial discourse. Numéro de notice : A2018-524 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1498503 Date de publication en ligne : 30/07/2018 En ligne : https://doi.org/10.1080/13658816.2018.1498503 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91349
in International journal of geographical information science IJGIS > vol 32 n° 11-12 (November - December 2018) . - pp 2247 - 2271[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018061 RAB Revue Centre de documentation En réserve L003 Disponible Formal representation of qualitative direction / Christian Freksa in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)
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Titre : Formal representation of qualitative direction Type de document : Article/Communication Auteurs : Christian Freksa, Auteur ; Jasper van de Ven, Auteur ; Diedrich Wolter, Auteur Année de publication : 2018 Article en page(s) : pp 2514 - 2534 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] direction
[Termes IGN] raisonnement spatial
[Termes IGN] représentation cartographique
[Termes IGN] représentation spatiale
[Termes IGN] traitement de données localiséesRésumé : (Auteur) This paper reviews formal approaches to representing spatial knowledge about qualitative direction. Unlike geometric direction information, qualitative information does not employ numerical values but relies on comparison. The qualitative approach is often regarded as suitable for capturing commonsense concepts and thus is relevant to human-centered interfaces for spatial information systems. To establish a context for the work on qualitative direction, we preset a brief history of the development of qualitative temporal and spatial representations from different scientific perspectives. We identify main focal areas of these representations of spatial direction and propose a taxonomy. In the light of more than three decades of fruitful research, we obtain a map of formal representations that reveal interrelationships between different research strands in the field. Numéro de notice : A2018-528 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1420794 Date de publication en ligne : 25/01/2018 En ligne : https://doi.org/10.1080/13658816.2017.1420794 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91366
in International journal of geographical information science IJGIS > vol 32 n° 11-12 (November - December 2018) . - pp 2514 - 2534[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018061 RAB Revue Centre de documentation En réserve L003 Disponible A hybrid ensemble learning method for tourist route recommendations based on geo-tagged social networks / Lin Wan in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)
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Titre : A hybrid ensemble learning method for tourist route recommendations based on geo-tagged social networks Type de document : Article/Communication Auteurs : Lin Wan, Auteur ; Yuming Hong, Auteur ; Zhou Huang, Auteur ; Xia Peng, Auteur ; Ran Li, Auteur Année de publication : 2018 Article en page(s) : pp 2225 - 2246 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] apprentissage automatique
[Termes IGN] calcul d'itinéraire
[Termes IGN] classification bayesienne
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées des bénévoles
[Termes IGN] données météorologiques
[Termes IGN] exploration de données géographiques
[Termes IGN] géobalise
[Termes IGN] image Flickr
[Termes IGN] Pékin (Chine)
[Termes IGN] point d'intérêtRésumé : (Auteur) Geo-tagged travel photos on social networks often contain location data such as points of interest (POIs), and also users’ travel preferences. In this paper, we propose a hybrid ensemble learning method, BAyes-Knn, that predicts personalized tourist routes for travelers by mining their geographical preferences from these location-tagged data. Our method trains two types of base classifiers to jointly predict the next travel destination: (1) The K-nearest neighbor (KNN) classifier quantifies users’ location history, weather condition, temperature and seasonality and uses a feature-weighted distance model to predict a user’s personalized interests in an unvisited location. (2) A Bayes classifier introduces a smooth kernel function to estimate a-priori probabilities of features and then combines these probabilities to predict a user’s latent interests in a location. All the outcomes from these subclassifiers are merged into one final prediction result by using the Borda count voting method. We evaluated our method on geo-tagged Flickr photos and Beijing weather data collected from 1 January 2005 to 1 July 2016. The results demonstrated that our ensemble approach outperformed 12 other baseline models. In addition, the results showed that our framework has better prediction accuracy than do context-aware significant travel-sequence-patterns recommendations and frequent travel-sequence patterns. Numéro de notice : A2018-523 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1458988 Date de publication en ligne : 03/05/2018 En ligne : https://doi.org/10.1080/13658816.2018.1458988 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91348
in International journal of geographical information science IJGIS > vol 32 n° 11-12 (November - December 2018) . - pp 2225 - 2246[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018061 RAB Revue Centre de documentation En réserve L003 Disponible A topology-preserving polygon rasterization algorithm / Chen Zhou in Cartography and Geographic Information Science, Vol 45 n° 6 (November 2018)
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Titre : A topology-preserving polygon rasterization algorithm Type de document : Article/Communication Auteurs : Chen Zhou, Auteur ; Dingmou Li, Auteur ; Ningchuan Xiao, Auteur ; Zhenjie Chen, Auteur ; Xiang Li, Auteur ; Manchun Li, Auteur Année de publication : 2018 Article en page(s) : pp 495 - 509 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] données vectorielles
[Termes IGN] polygone
[Termes IGN] rastérisation
[Termes IGN] relation topologique
[Termes IGN] traitement de données localiséesRésumé : (Auteur) Conventional algorithms for polygon rasterization are typically designed to maintain non-topological characteristics. Consequently, topological relationships, such as the adjacency between polygons, may also be lost or altered, creating topological errors. This paper proposes a topology-preserving polygon rasterization algorithm to avoid topological errors. Four types of topological error may occur during polygon rasterization. The algorithm starts from an initial polygon rasterization and uses a set of preserving strategies to increase topological accuracy. The count of the four types of error measures the topological errors of the conversion. Topological accuracy is summarized as 1 minus the ratio of actual topological errors to the total number of possible error cases. When applied to a land-use dataset with a data volume of 128 MB, 127,836 polygons, and extending 1352 km2, the algorithm achieves a topological accuracy of more than 99% when raster cell size is 30 m or smaller (100% for 5 and 10 m). The effects of cell size, polygon shape, and number of iterations on topological accuracy are also examined. Numéro de notice : A2018-473 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1401488 Date de publication en ligne : 21/11/2017 En ligne : https://doi.org/10.1080/15230406.2017.1401488 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91256
in Cartography and Geographic Information Science > Vol 45 n° 6 (November 2018) . - pp 495 - 509[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2018061 RAB Revue Centre de documentation En réserve L003 Disponible Toward a participatory VGI methodology : crowdsourcing information on regional food assets / Victoria Fast in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)
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Titre : Toward a participatory VGI methodology : crowdsourcing information on regional food assets Type de document : Article/Communication Auteurs : Victoria Fast, Auteur ; Claus Rinner, Auteur Année de publication : 2018 Article en page(s) : pp 2209 - 2224 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] alimentation
[Termes IGN] données localisées des bénévoles
[Termes IGN] exploitation agricole
[Termes IGN] participation du public
[Termes IGN] production participative
[Termes IGN] SIG participatifRésumé : (Auteur) Local knowledge has been underrepresented in food-related policies and planning. The goal of this research was to engage members of a local food community and generate volunteered geographic information (VGI) on community food assets. During active data collection, over 200 food assets were reported. This paper details the systematic approach used to create VGI, which emphasizes the socio-cultural context surrounding the mapping technology. The project began with an identified need to connect to and learn from the local food community. The participants were drawn from active food system stakeholders, and a Geoweb infrastructure was selected based on publicly available crowdsourcing tools. The resulting VGI is presented according to system functions: input (Web traffic, contributors, input types), management (contribution vetting, privacy), analysis (typology of input), and presentation (sharing the submitted data). Despite limitations, this study revealed a hyper-local and community-driven perspective on food assets, opened access to government and private data, and increased the transparency and accessibility of information on the regional food system. This research also revealed that there is a growing need for intermediaries who can bridge the gap between experts in the subject matter and experts in digitally enabled participation, and a need for non-government open data repositories. Numéro de notice : A2018-522 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1480784 Date de publication en ligne : 05/06/2018 En ligne : https://doi.org/10.1080/13658816.2018.1480784 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91347
in International journal of geographical information science IJGIS > vol 32 n° 11-12 (November - December 2018) . - pp 2209 - 2224[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018061 RAB Revue Centre de documentation En réserve L003 Disponible Uncertainty modeling and analysis of surface area calculation based on a regular grid digital elevation model (DEM) / Chang Li in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)PermalinkInterplay between urban communities and human‐crowd mobility: A study using contributed geospatial data sources / Mohammad Forghani in Transactions in GIS, vol 22 n° 4 (August 2018)PermalinkProcessing BIM and GIS models in practice: Experiences and recommendations from a geoBIM project in The Netherlands / Ken Arroyo Ohori in ISPRS International journal of geo-information, vol 7 n° 8 (August 2018)PermalinkPermalink«Blockchain» et géomatique / Anonyme in Géomatique expert, n° 122 (mai-juin 2018)PermalinkLe FOSS4G-fr version 2018 / Anonyme in Géomatique expert, n° 122 (mai-juin 2018)PermalinkL’opérateur de collage : Gestion de plusieurs points de vue dans un contexte spatial / Géraldine Del Mondo in Revue internationale de géomatique, vol 28 n° 3 (juillet - septembre 2018)PermalinkDe la navigation connectée à la voiture autonome - partie 2 Et mon tout est un véhicule autonome / Hubert d' Erceville in SIGmag, n° 17 (juin 2018)PermalinkEfficient task assignment in spatial crowdsourcing with worker and task privacy protection / An Liu in Geoinformatica, vol 22 n° 2 (April 2018)PermalinkJournées de la recherche IGN 2018 / Anonyme in Géomatique expert, n° 121 (mars - avril 2018)Permalink