2012 16th Panhellenic Conference on Informatics (2011)
Sept. 30, 2011 to Oct. 2, 2011
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PCI.2011.22
One of the common queries in spatial databases is the (K) Nearest Neighbor Query that discovers the (K) closest objects to a query object. Processing of spatial queries, in most cases, is accomplished by indexing spatial data by an access method. In this paper, we present algorithms for Nearest Neighbor Queries using a disk based structure that belongs to the Quad tree family, the xBR-tree, that can be used for indexing large point datasets. We demonstrate performance results (I/O efficiency and execution time) of alternative Nearest Neighbor algorithms, using real datasets.
Spatial Access Methods, Quadtrees, Nearest Neighbor Query, Query Processing
George Roumelis, Michael Vassilakopoulos, Antonio Corral, "Nearest Neighbor Algorithms Using xBR-Trees", 2012 16th Panhellenic Conference on Informatics, vol. 00, no. , pp. 51-55, 2011, doi:10.1109/PCI.2011.22