TY - GEN
T1 - Efficient difference NN queries for moving objects
AU - Wang, Bin
AU - Yang, Xiaochun
AU - Wang, Guoren
AU - Yu, Ge
PY - 2007
Y1 - 2007
N2 - Group Nearest Neighbor query is a relatively prevalent application in spatial databases and overlay network. Unlike the traditional KNN queries, GNN queries maintain several query points and allow aggregate operations among them. Our paper proposes a novel approach for dealing with difference operation of GNN queries on multiple query points. Difference nearest neighbor (DNN) plays an important role on statistical analysis and engineer computation. Seldom existing approaches consider DNN queries. In our paper, we use the properties of hyperbola to efficiently solve DNN queries. A hyperbola divides the query space into several subspaces. Such properties can help us to prune the search spaces. However, the computation cost using hyperbola is not desirable since it is difficult to estimate spaces using curves. Therefore, we adopt asymptotes of hyperbola to simplify the hyperbola-based pruning strategy to reduce the computation cost and the search space. Our experimental results show that the proposed approaches can efficiently solve DNN queries.
AB - Group Nearest Neighbor query is a relatively prevalent application in spatial databases and overlay network. Unlike the traditional KNN queries, GNN queries maintain several query points and allow aggregate operations among them. Our paper proposes a novel approach for dealing with difference operation of GNN queries on multiple query points. Difference nearest neighbor (DNN) plays an important role on statistical analysis and engineer computation. Seldom existing approaches consider DNN queries. In our paper, we use the properties of hyperbola to efficiently solve DNN queries. A hyperbola divides the query space into several subspaces. Such properties can help us to prune the search spaces. However, the computation cost using hyperbola is not desirable since it is difficult to estimate spaces using curves. Therefore, we adopt asymptotes of hyperbola to simplify the hyperbola-based pruning strategy to reduce the computation cost and the search space. Our experimental results show that the proposed approaches can efficiently solve DNN queries.
UR - http://www.scopus.com/inward/record.url?scp=38049030208&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-72524-4_56
DO - 10.1007/978-3-540-72524-4_56
M3 - Conference contribution
AN - SCOPUS:38049030208
SN - 9783540724834
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 542
EP - 553
BT - Advances in Data and Web Management - Joint 9th Asia-Pacific Web Conference, APWeb 2007 and 8th International Conference on Web-Age Information Management, WAIM 2007, Proceedings
PB - Springer Verlag
T2 - Joint 9th Asia-Pacific Web Conference on Advances in Data and Web Management, APWeb 2007 and 8th International Conference on Web-Age Information Management, WAIM 2007
Y2 - 16 June 2007 through 18 June 2007
ER -