Centre de documentation
scientifique

Snapshot and continuous points-based trajectory search / Shuyao Qi in Geoinformatica, vol 21 n° 4 (October - December 2017)  

Public [article]  inGeoinformatica > vol 21 n° 4 (October - December 2017) . - pp 669 - 701 Titre : Snapshot and continuous points-based trajectory search Type de document : Article/Communication Auteurs : Shuyao Qi, Auteur ; Dimitri Sacharidis, Auteur ; Panagiotis Bouros, Auteur ; Nikos Mamoulis, Auteur Année de publication : 2017 Article en page(s) : pp 669 - 701 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse combinatoire (maths) [Termes IGN] calcul d'itinéraire [Termes IGN] distance [Termes IGN] plus proche voisin, algorithme du [Termes IGN] temps [Termes IGN] temps instantané [Termes IGN] théorie des possibilités Résumé : (Auteur) Trajectory data capture the traveling history of moving objects such as people or vehicles. With the proliferation of GPS and tracking technologies, huge volumes of trajectories are rapidly generated and collected. Under this, applications such as route recommendation and traveling behavior mining call for efficient trajectory retrieval. In this paper, we first focus on distance-to-points trajectory search; given a collection of trajectories and a set query points, the goal is to retrieve the top-k trajectories that pass as close as possible to all query points. We advance the state-of-the-art by combining existing approaches to a hybrid nearest neighbor-based method while also proposing an alternative, more efficient spatial range-based approach. Second, we investigate the continuous counterpart of distance-to-points trajectory search where the query is long-standing and the set of returned trajectories needs to be maintained whenever updates occur to the query and/or the data. Third, we propose and study two practical variants of distance-to-points trajectory search, which take into account the temporal characteristics of the searched trajectories. Through an extensive experimental analysis with real trajectory data, we show that our range-based approach outperforms previous methods by at least one order of magnitude for the snapshot and up to several times for the continuous version of the queries. Numéro de notice : A2017-600 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0267-9 En ligne : https://doi.org/10.1007/s10707-016-0267-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86908 [article]

Index-based query processing on distributed multidimensional data / George Tsatsanifos in Geoinformatica, vol 17 n° 3 (July 2013)  

Public [article]  inGeoinformatica > vol 17 n° 3 (July 2013) . - pp 489 - 519 Titre : Index-based query processing on distributed multidimensional data Type de document : Article/Communication Auteurs : George Tsatsanifos, Auteur ; Dimitri Sacharidis, Auteur ; Timos Sellis, Auteur Année de publication : 2013 Article en page(s) : pp 489 - 519 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] base de données répartie [Termes IGN] données multidimensionnelles [Termes IGN] index spatial [Termes IGN] requête spatiale Résumé : (Auteur) This work introduces decentralized query processing techniques based on MIDAS, a novel distributed multidimensional index. In particular, MIDAS implements a distributed k-d tree, where leaves correspond to peers, and internal nodes dictate message routing. MIDAS requires that peers maintain little network information, and features mechanisms that support fault tolerance and load balancing. The proposed algorithms process point and range queries over the multidimensional indexed space in only O(log n) hops in expectance, where n is the network size. For nearest neighbor queries, two processing alternatives are discussed. The first, termed eager processing, has low latency (expected value of O(log n) hops) but may involve a large number of peers. The second, termed iterative processing, has higher latency (expected value of O(log2 n) hops) but involves far fewer peers. A detailed experimental evaluation demonstrates that our query processing techniques outperform existing methods for settings involving real spatial data as well as in the case of high dimensional synthetic data. Numéro de notice : A2013-383 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-012-0163-x Date de publication en ligne : 09/08/2012 En ligne : https://doi.org/10.1007/s10707-012-0163-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32521 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-2013031	RAB	Revue	Centre de documentation	En réserve L003	Disponible