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Efficient maximal reverse skyline query processing / Farnoush Banaei-Kashani in Geoinformatica, vol 21 n° 3 (July - September 2017)
[article]
Titre : Efficient maximal reverse skyline query processing Type de document : Article/Communication Auteurs : Farnoush Banaei-Kashani, Auteur ; Parisa Ghaemi, Auteur ; Bahman Movaqar, Auteur ; Seyed Jalal Kazemitabar, Auteur Année de publication : 2017 Article en page(s) : pp 549 - 572 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] analyse multicritère
[Termes IGN] espace métrique
[Termes IGN] jeu de données localisées
[Termes IGN] opérateur skyline
[Termes IGN] requête (informatique)
[Termes IGN] requête spatiale inverseRésumé : (Auteur) Given a set S of sites and a set O of objects in a metric space, the Optimal Location (OL) problem is about computing a location in the space where introducing a new site (e.g., a retail store) maximizes the number of the objects (e.g., customers) that would choose the new site as their “preferred” site among all sites. However, the existing solutions for the optimal location problem assume that there is only one criterion to determine the preferred site for each object, whereas with numerous real-world applications multiple criteria are used as preference measures. For example, while a single criterion solution might consider the metric distance between the customers and the retail store as the preference measure, a multi-criteria solution might consider the annual membership cost as well as the distance to the retail store to find an optimal location. In this paper, for the first time we develop an efficient and exact solution for the so-called Multi-Criteria Optimal Location (MCOL) problem that can scale with large datasets. Toward that end, first we formalize the MCOL problem as maximal reverse skyline query (MaxRSKY). Given a set of sites and a set of objects in a d-dimensional space, MaxRSKY query returns a location in the space where if a new site s is introduced, the size of the (bichromatic) reverse skyline set of s is maximal. To the best of our knowledge, this paper is the first to define and study MaxRSKY query. Accordingly, we propose a filter-based solution, termed EF-MaxRSKY, that effectively prunes the search space for efficient identification of the optimal location. Our extensive empirical analysis with both real and synthetic datasets show that EF-MaxRSKY is invariably efficient in computing answers for MaxRSKY queries with large datasets containing thousands of sites and objects. Numéro de notice : A2017-381 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-017-0302-5 En ligne : https://doi.org/10.1007/s10707-017-0302-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85812
in Geoinformatica > vol 21 n° 3 (July - September 2017) . - pp 549 - 572[article]On reverse-k-nearest-neighbor joins / Tobias Emrich in Geoinformatica, vol 19 n° 2 (April - June 2015)
[article]
Titre : On reverse-k-nearest-neighbor joins Type de document : Article/Communication Auteurs : Tobias Emrich, Auteur ; Hans-Peter Kriege, Auteur ; Peer Kröger, Auteur ; et al., Auteur Année de publication : 2015 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse comparative
[Termes IGN] classification barycentrique
[Termes IGN] espace métrique
[Termes IGN] espace vectoriel
[Termes IGN] jointure spatiale
[Termes IGN] requête (informatique)
[Termes IGN] requête spatiale inverseRésumé : (auteur) A reverse k-nearest neighbour (RkNN) query determines the objects from a database that have the query as one of their k-nearest neighbors. Processing such a query has received plenty of attention in research. However, the effect of running multiple RkNN queries at once (join) or within a short time interval (bulk/group query) has only received little attention so far. In this paper, we analyze different types of RkNN joins and provide a classification of existing RkNN join algorithms. We discuss possible solutions for solving the non-trivial variants of the problem in vector spaces, including self and mutual pruning strategies. Further, we generalize the developed algorithms to general metric spaces. During an extensive performance analysis we provide evaluation results showing the IO and CPU performance of the compared algorithms for a wide range of different setups and suggest appropriate query algorithms for specific scenarios. Numéro de notice : A2015-490 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-014-0215-5 Date de publication en ligne : 23/08/2014 En ligne : https://doi.org/10.1007/s10707-014-0215-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77283
in Geoinformatica > vol 19 n° 2 (April - June 2015)[article]
[article]
Titre : Spatial inverse query processing Type de document : Article/Communication Auteurs : Thomas Bernecker, Auteur ; Tobias Emrich, Auteur ; Hans-Peter Kriegel, Auteur ; Nikos Mamoulis, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 449 - 487 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] requête spatiale
[Termes IGN] requête spatiale inverseRésumé : (Auteur) Traditional spatial queries return, for a given query object q, all database objects that satisfy a given predicate, such as epsilon range and k-nearest neighbors. This paper defines and studies inverse spatial queries, which, given a subset of database objects Q and a query predicate, return all objects which, if used as query objects with the predicate, contain Q in their result. We first show a straightforward solution for answering inverse spatial queries for any query predicate. Then, we propose a filter-and-refinement framework that can be used to improve efficiency. We show how to apply this framework on a variety of inverse queries, using appropriate space pruning strategies. In particular, we propose solutions for inverse epsilon range queries, inverse k-nearest neighbor queries, and inverse skyline queries. Furthermore, we show how to relax the definition of inverse queries in order to ensure non-empty result sets. Our experiments show that our framework is significantly more efficient than naive approaches. Numéro de notice : A2013-382 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-012-0162-y Date de publication en ligne : 24/08/2012 En ligne : https://doi.org/10.1007/s10707-012-0162-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32520
in Geoinformatica > vol 17 n° 3 (July 2013) . - pp 449 - 487[article]Réservation
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