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Using textual volunteered geographic information to model nature-based activities: A case study from Aotearoa New Zealand / Ekaterina Egorova in Journal of Spatial Information Science, JoSIS, n° 23 (2021)  

Public [article]  inJournal of Spatial Information Science, JoSIS > n° 23 (2021) . - pp 25 - 63 Titre : Using textual volunteered geographic information to model nature-based activities: A case study from Aotearoa New Zealand Type de document : Article/Communication Auteurs : Ekaterina Egorova, Auteur Année de publication : 2021 Article en page(s) : pp 25 - 63 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cognition [Termes IGN] corpus [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] données localisées des bénévoles [Termes IGN] émotion [Termes IGN] interaction homme-milieu [Termes IGN] littérature [Termes IGN] loisir [Termes IGN] milieu naturel [Termes IGN] Nouvelle-Zélande [Termes IGN] réseau social [Termes IGN] service écosystémique Résumé : (auteur) A boom in volunteered geographic information has led to extensive data-driven exploration and modeling of places. While many studies have used such data to explore human-environment interaction in urban settings, few have investigated natural, non-urban settings. To address this gap, this study systematically explores the content of online reviews of nature-based recreation activities, and develops a fine-grained hierarchical model that includes 28 aspects grouped into three main domains: activity, settings, and emotions/cognition. It further demonstrates how the model can be used to explore the variation in recreation experiences across activities, setting the stage for the analysis of the spatio-temporal variations in recreation experiences in the future. Importantly, the study provides an annotated corpus that can be used as a training dataset for developing methods to automatically capture aspects of recreation experiences in texts. Numéro de notice : A2021-950 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.5311/JOSIS.2021.23.157 Date de publication en ligne : 24/12/2021 En ligne : https://doi.org/10.5311/JOSIS.2021.23.157 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99644 [article]

Fictive motion extraction and classification / Ekaterina Egorova in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 11-12 (November - December 2018) . - pp 2247 - 2271 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 naturel Résumé : (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 [article]

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