Title :
V*-kNN: An Efficient Algorithm for Moving k Nearest Neighbor Queries
Author :
Nutanong, Sarana ; Zhang, Rui ; Tanin, Egemen ; Kulik, Lars
Author_Institution :
Dept. of Comput. Sci. & Software Eng., Univ. of Melbourne, Melbourne, VIC
fDate :
March 29 2009-April 2 2009
Abstract :
This demonstration program presents the V*-kNN algorithm, an efficient algorithm to process moving k nearest neighbor queries (MkNN). The V*-kNN algorithm is based on a safe-region concept called the V*-Diagram. By incrementally maintaining the V*-Diagram, V*-kNN continuously provides accurate MkNN query results and supports dynamically changing values of k. Our approach exploits information regarding the current location of the query point and the search space in addition to the data objects. As a result, the V*-kNN has much smaller IO and computation costs than existing methods.
Keywords :
pattern clustering; query processing; MkNN query; V*-Diagram; V*-kNN algorithm; moving k nearest neighbor queries; search space; Computational efficiency; Computer science; Data engineering; Information retrieval; Laboratories; Nearest neighbor searches; Neural networks; Software algorithms; Software engineering; USA Councils;
Conference_Titel :
Data Engineering, 2009. ICDE '09. IEEE 25th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3422-0
Electronic_ISBN :
1084-4627
DOI :
10.1109/ICDE.2009.63