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Auteur Chaowei Yang |
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Forming a global monitoring mechanism and a spatiotemporal performance model for geospatial services / Jizhe Xia in International journal of geographical information science IJGIS, vol 29 n° 3 (March 2015)
[article]
Titre : Forming a global monitoring mechanism and a spatiotemporal performance model for geospatial services Type de document : Article/Communication Auteurs : Jizhe Xia, Auteur ; Chaowei Yang, Auteur ; K. Liu, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 375 - 396 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] architecture orientée services
[Termes IGN] données massives
[Termes IGN] évaluation
[Termes IGN] informatique en nuage
[Termes IGN] infrastructure mondiale des données localisées
[Termes IGN] modèle conceptuel de données spatio-temporelles
[Termes IGN] service web géographique
[Termes IGN] test de performanceRésumé : (Auteur) Geographic information service (GIService) has become popular in the last decade to develop applications for addressing global challenges. Performance is one of the most important criteria to help users select distributed online GIService for developing geospatial applications including natural hazards and emergency responses. However, performance accuracy is limited by the single-location-based evaluation mechanism while service performance is dynamic in space and time between end-users and services. We propose a spatiotemporal performance evaluation mechanism to improve the accuracy. Specially, a cloud and volunteer computing mechanism is proposed to collect performance information of globally distributed GIServices. A global spatiotemporal performance model is designed to integrate spatiotemporal dynamics for better performance evaluation for users from different regions at different times. This model is tested to support GIService selection in global spatial data infrastructures (SDIs). The experiment confirms that the proposed model provides more accurate evaluations for global users and better supports geospatial resource utilizations in SDIs than previous mechanisms. The methodology can be adopted to improve the services of other regional and global distributed operational systems. Numéro de notice : A2015-583 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.968783 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2014.968783 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77869
in International journal of geographical information science IJGIS > vol 29 n° 3 (March 2015) . - pp 375 - 396[article]Evaluating the “geographical awareness” of individuals: an exploratory analysis of Twitter data / Chen Xu in Cartography and Geographic Information Science, vol 40 n° 2 (March 2013)
[article]
Titre : Evaluating the “geographical awareness” of individuals: an exploratory analysis of Twitter data Type de document : Article/Communication Auteurs : Chen Xu, Auteur ; David W. Wong, Auteur ; Chaowei Yang, Auteur Année de publication : 2013 Article en page(s) : pp 103 - 115 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatiale
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] échantillonnage
[Termes IGN] exploration de données géographiques
[Termes IGN] extraction de données
[Termes IGN] fiabilité des données
[Termes IGN] géopositionnement
[Termes IGN] langage naturel (informatique)
[Termes IGN] qualité des donnéesRésumé : (Auteur) A major theme in the geographical studies of social media content such as tweets from Twitter is to extract the locations of content providers (e.g., Twitter users) in order to track their movements or activity patterns. This framework also has been used to detect the dispersion of ideas over space and time. Another theme is to assess how the interaction of these providers may vary between the physical and virtual spaces. However, few geographical studies have explored if social media content can be used to examine the relationship between the characteristics of content providers and their geographical knowledge at different spatial scales. We expected that in general, one's awareness of the local geography should be higher than that of places farther away. In this paper, we explored if such pattern of geographical awareness in the physical space is reflected in the social media content. We reported our detailed examinations of tweets from a set of individuals who have provided substantial information in their profiles. Using text-mining methods, including natural language processing (NLP) techniques, we identified place names mentioned in the tweets and geocoded them. These locations were analyzed in a geographical-hierarchical manner to build a geographical awareness profile for each individual. While these geographical awareness profiles vary quite dramatically, their variations can be explained by the users’ characteristics, which were interpreted from their tweet content. This study demonstrates how social media content may be used to assess the geographical awareness characteristics of a biased sample population. Numéro de notice : A2013-745 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2013.776212 En ligne : https://doi.org/10.1080/15230406.2013.776212 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32881
in Cartography and Geographic Information Science > vol 40 n° 2 (March 2013) . - pp 103 - 115[article]Exemplaires(1)
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