Abstract
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.
Supported by the 973 Program under Grant No. 2006CB303103, the Natural Science Foundation of China under Grant Nos.60503036, 60473074, 60573089, and the Fok Ying Tong Education Foundation of China under Grant No. 104027.
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Wang, B., Yang, X., Wang, G., Yu, G. (2007). Efficient Difference NN Queries for Moving Objects. In: Dong, G., Lin, X., Wang, W., Yang, Y., Yu, J.X. (eds) Advances in Data and Web Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72524-4_56
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