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The direction-constrained k nearest neighbor query dealing with spatio-directional objects / Min-Joong Lee in Geoinformatica, vol 20 n° 3 (July - September 2016)  

Public [article]  inGeoinformatica > vol 20 n° 3 (July - September 2016) . - pp 471 – 502 Titre : The direction-constrained k nearest neighbor query dealing with spatio-directional objects Type de document : Article/Communication Auteurs : Min-Joong Lee, Auteur ; Dong-Wan Choi, Auteur ; SangYeon Kim, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 471 – 502 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] analyse coût-avantage [Termes IGN] classification barycentrique [Termes IGN] données massives [Termes IGN] index spatial [Termes IGN] objet géographique [Termes IGN] plus proche voisin, algorithme du [Termes IGN] requête spatiale Résumé : (auteur) Finding k nearest neighbor objects in spatial databases is a fundamental problem in many geospatial systems and the direction is one of the key features of a spatial object. Moreover, the recent tremendous growth of sensor technologies in mobile devices produces an enormous amount of spatio-directional (i.e., spatially and directionally encoded) objects such as photos. Therefore, an efficient and proper utilization of the direction feature is a new challenge. Inspired by this issue and the traditional k nearest neighbor search problem, we devise a new type of query, called the direction-constrained k nearest neighbor (DCkNN) query. The DCkNN query finds k nearest neighbors from the location of the query such that the direction of each neighbor is in a certain range from the direction of the query. We develop a new index structure called MULTI, to efficiently answer the DCkNN query with two novel index access algorithms based on the cost analysis. Furthermore, our problem and solution can be generalized to deal with spatio-circulant dimensional (such as a direction and circulant periods of time such as an hour, a day, and a week) objects. Experimental results show that our proposed index structure and access algorithms outperform two adapted algorithms from existing kNN algorithms. Numéro de notice : A2016-378 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0245-2 En ligne : http://dx.doi.org/10.1007/s10707-016-0245-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81145 [article]