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Finding dense locations in symbolic indoor tracking data: modeling, indexing, and processing / Tanvir Ahmed in Geoinformatica, vol 21 n° 1 (January - March 2017)  

Public [article]  inGeoinformatica > vol 21 n° 1 (January - March 2017) . - pp 119 - 150 Titre : Finding dense locations in symbolic indoor tracking data: modeling, indexing, and processing Type de document : Article/Communication Auteurs : Tanvir Ahmed, Auteur ; Toren Bach Pedersen, Auteur ; Hua Lu, Auteur Année de publication : 2017 Article en page(s) : pp 119 - 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] données spatiotemporelles [Termes IGN] géolocalisation [Termes IGN] index spatial [Termes IGN] positionnement en intérieur [Termes IGN] requête spatiale [Termes IGN] système de gestion de bases de données relationnelles Résumé : (auteur) Finding the dense locations in large indoor spaces is very useful for many applications such as overloaded area detection, security control, crowd management, indoor navigation, and so on. Indoor tracking data can be enormous and are not immediately ready for finding dense locations. This paper presents two graph-based models for constrained and semi-constrained indoor movement, respectively, and then uses the models to map raw tracking records into mapping records that represent object entry and exit times in particular locations. Subsequently, an efficient indexing structure called Hierarchical Dense Location Time Index (HDLT-Index) is proposed for indexing the time intervals of the mapping table, along with index construction, query processing, and pruning techniques. The HDLT-Index supports very efficient aggregate point, interval, and duration queries as well as dense location queries. A comprehensive experimental study with both real and synthetic data shows that the proposed techniques are efficient and scalable and outperforms RDBMSs significantly. Numéro de notice : A2017-026 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0276-8 En ligne : http://dx.doi.org/10.1007/s10707-016-0276-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83977 [article]

A probabilistic data model and algebra for location-based data warehouses and their implementation / Igor Timko in Geoinformatica, vol 18 n° 2 (April 2014)  

Public [article]  inGeoinformatica > vol 18 n° 2 (April 2014) . - pp 357 - 404 Titre : A probabilistic data model and algebra for location-based data warehouses and their implementation Type de document : Article/Communication Auteurs : Igor Timko, Auteur ; Curtis Dyreson, Auteur ; Toren Bach Pedersen, Auteur Année de publication : 2014 Article en page(s) : pp 357 - 404 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] base de données localisées [Termes IGN] entrepôt de données [Termes IGN] incertitude des données [Termes IGN] modèle stochastique [Termes IGN] service fondé sur la position [Termes IGN] SOLAP Résumé : (Auteur) This paper proposes a novel, probabilistic data model and algebra that improves the modeling and querying of uncertain data in spatial OLAP (SOLAP) to support location-based services. Data warehouses that support location-based services need to combine complex hierarchies, such as road networks or transportation infrastructures, with static and dynamic content, e.g., speed limits and vehicle positions, respectively. Both the hierarchies and the content are often uncertain in real-world applications. Our model supports the use of probability distributions within both facts and dimensions. We give an algebra that correctly aggregates uncertain data over uncertain hierarchies. This paper also describes an implementation of the model and algebra, gives a complexity analysis of the algebra, and reports on an empirical, experimental evaluation of the implementation. The work is motivated with a real-world case study, based on our collaboration with a leading Danish vendor of location-based services. Numéro de notice : A2014-229 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-013-0180-4 Date de publication en ligne : 21/05/2013 En ligne : https://doi.org/10.1007/s10707-013-0180-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33132 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-2014021	RAB	Revue	Centre de documentation	En réserve L003	Disponible