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A comparative study of two approaches for supporting optimal network location queries / Parisa Ghaemi in Geoinformatica, vol 18 n° 2 (April 2014)
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Titre : A comparative study of two approaches for supporting optimal network location queries Type de document : Article/Communication Auteurs : Parisa Ghaemi, Auteur ; Kaveh Shahabi, Auteur ; John P. Wilson, Auteur ; Farnoush Banaei-Kashani, Auteur Année de publication : 2014 Article en page(s) : pp 229 - 251 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse comparative
[Termes IGN] base de données spatiotemporelles
[Termes IGN] distance
[Termes IGN] étude d'implantation
[Termes IGN] géomercatique
[Termes IGN] optimisation (mathématiques)
[Termes IGN] requête spatiale
[Termes IGN] réseau routierRésumé : (Auteur) Given a set S of sites and a set O of weighted objects, an optimal location query finds the location(s) where introducing a new site maximizes the total weight of the objects that are closer to the new site than to any other site. With such a query, for instance, a franchise corporation (e.g., McDonald’s) can find a location to open a new store such that the number of potential store customers (i.e., people living close to the store) is maximized. Optimal location queries are computationally complex to compute and require efficient solutions that scale with large datasets. Previously, two specific approaches have been proposed for efficient computation of optimal location queries. However, they both assume p-norm distance (namely, L1 and L2/Euclidean); hence, they are not applicable where sites and objects are located on spatial networks. In this article, we focus on optimal network location (ONL) queries, i.e., optimal location queries in which objects and sites reside on a spatial network. We introduce two complementary approaches, namely EONL (short for Expansion-based ONL) and BONL (short for Bound-based ONL), which enable efficient computation of ONL queries with datasets of uniform and skewed distributions, respectively. Moreover, with an extensive experimental study, we verify and compare the efficiency of our proposed approaches with real world datasets, and we demonstrate the importance of considering network distance (rather than p-norm distance) with ONL queries. Numéro de notice : A2014-225 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-013-0179-x Date de publication en ligne : 28/04/2013 En ligne : https://doi.org/10.1007/s10707-013-0179-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33128
in Geoinformatica > vol 18 n° 2 (April 2014) . - pp 229 - 251[article]Réservation
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