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Processing optimal sequenced route queries using Voronoi diagrams / M. Sharifzadeh in Geoinformatica, vol 12 n° 4 (December 2008)  

Public [article]  inGeoinformatica > vol 12 n° 4 (December 2008) . - pp 411 - 433 Titre : Processing optimal sequenced route queries using Voronoi diagrams Type de document : Article/Communication Auteurs : M. Sharifzadeh, Auteur ; C. Shahabi, Auteur Année de publication : 2008 Article en page(s) : pp 411 - 433 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] calcul d'itinéraire [Termes IGN] diagramme de Voronoï [Termes IGN] espace métrique [Termes IGN] recherche du chemin optimal, algorithme de [Termes IGN] requête spatiale Résumé : (Auteur) The Optimal Sequenced Route (OSR) query strives to find a route of minimum length starting from a given source location and passing through a number of typed locations in a specific sequence imposed on the types of the locations. In this paper, we propose a pre-computation approach to OSR query in both vector and metric spaces. We exploit the geometric properties of the solution space and theoretically prove its relation to additively weighted Voronoi diagrams. Our approach recursively accesses these diagrams to incrementally build the OSR. Introducing the analogous diagrams for the space of road networks, we show that our approach is also efficiently applicable to this metric space. Our experimental results verify that our pre-computation approach outperforms the previous index-based approaches in terms of query response time. Copyright Springer Numéro de notice : A2008-377 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-007-0034-z En ligne : https://doi.org/10.1007/s10707-007-0034-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29370 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-08041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Utilizing Voronoi cells of location data streams for accurate computation of aggregate functions in sensor networks / M. Sharifzadeh in Geoinformatica, vol 10 n° 1 (March - May 2006)  

Public [article]  inGeoinformatica > vol 10 n° 1 (March - May 2006) Titre : Utilizing Voronoi cells of location data streams for accurate computation of aggregate functions in sensor networks Type de document : Article/Communication Auteurs : M. Sharifzadeh, Auteur ; C. Shahabi, Auteur Année de publication : 2006 Conférence : ACM GIS 2004, 12th ACM symposium on geographic information systems 12/11/2004 13/11/2004 Arlington Etats-Unis Selected papers Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] agrégation spatiale [Termes IGN] analyse comparative [Termes IGN] diagramme de Voronoï [Termes IGN] données vectorielles [Termes IGN] interpolation spatiale [Termes IGN] requête spatiale [Termes IGN] réseau de capteurs [Termes IGN] Triangulated Irregular Network Résumé : (Auteur) Sensor networks are unattended deeply distributed systems whose database schema can be conceptualized using the relational model. Aggregation queries on the data sampled at each sensor node are the main means to extract the abstract characteristics of the surrounding environment. However, the non-uniform distribution of the sensor nodes in the environment leads to inaccurate results generated by the aggregation queries. In this paper, we introduce "spatial aggregations" that take into consideration the spatial location of each measurement generated by the sensor nodes. We propose the use of spatial interpolation methods derived from the fields of spatial statistics and computational geometry to answer spatial aggregations. In particular, we study Spatial Moving Average (SMA), Voronoi Diagram and Triangulated Irregular Network (TIN). Investigating these methods for answering spatial average queries, we show that the average value on the data samples weighted by the area of the Voronoi cell of the corresponding sensor node, provides the best precision. Consequently, we introduce an algorithm to compute and maintain the accurate Voronoi cell at each sensor node while the location of the others arrive on data stream. We also propose AVC-SW, a novel algorithm to approximate this Voronoi cell over a sliding window that supports dynamism in the sensor network. To demonstrate the performance of in-network implementation of our aggregation operators, we have developed prototypes of two different approaches to distributed spatial aggregate processing. Numéro de notice : A2006-096 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1007/s10707-005-4884-y En ligne : https://doi.org/10.1007/s10707-005-4884-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27823 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-06011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A road network embedding technique for k-nearest neighbor search in moving object databases / M.R. Kolahdouzan in Geoinformatica, vol 7 n° 3 (September - November 2003)  

Public [article]  inGeoinformatica > vol 7 n° 3 (September - November 2003) . - pp 255 - 273 Titre : A road network embedding technique for k-nearest neighbor search in moving object databases Type de document : Article/Communication Auteurs : M.R. Kolahdouzan, Auteur ; C. Shahabi, Auteur ; M. Sharifzadeh, Auteur Année de publication : 2003 Conférence : ACM GIS 2002, 10th ACM International Symposium on Advances in Geographic Information Systems 08/11/2002 09/11/2002 McLean Virginie - Etats-Unis Selected papers Article en page(s) : pp 255 - 273 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] base de données localisées [Termes IGN] classification barycentrique [Termes IGN] distance euclidienne [Termes IGN] espace euclidien [Termes IGN] mise à jour de base de données [Termes IGN] réseau routier [Termes IGN] système d'information géographique [Termes IGN] topologie Résumé : (Auteur) A very important class of queries in GIS applications is the class of Knearest neighbor queries. Most of the current studies on the Knearest neighbor queries utilize spatial index structures and hence are based on the Euclidean distances between the points. In realworld road networks, however, the shortest distance between two points depends on the actual path connecting the points and cannot be computed accurately using one of the Minkowski metrics. Thus, the Euclidean distance may not properly approximate the real distance. In this paper, we apply an embedding technique to transform a road network to a high dimensional space in order to utilize computationally simple Minkowski metrics for distance measurement. Subsequently, we extend our approach to dynamically transform new points into the embedding space. Finally, we propose an efficient technique that can find the actual shortest path between two points in the original road network using only the embedding space. Our empirical experiments indicate that the Chessboard distance metric (L,) in the embedding space preserves the ordering of the distances between a point and its neighbors more precisely as compared to the Euclidean distance in the original road network. Numéro de notice : A2003-202 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1023/A:1025153016110 En ligne : https://doi.org/10.1023/A:1025153016110 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22498 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-03031	RAB	Revue	Centre de documentation	En réserve L003	Disponible