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SSDBM
2009
IEEE

Reverse k-Nearest Neighbor Search Based on Aggregate Point Access Methods

14 years 11 days ago
Reverse k-Nearest Neighbor Search Based on Aggregate Point Access Methods
Abstract. We propose an original solution for the general reverse k-nearest neighbor (RkNN) search problem in Euclidean spaces. Compared to the limitations of existing methods for the RkNN search, our approach works on top of MultiResolution Aggregate (MRA) versions of any index structures for multi-dimensional feature spaces where each non-leaf node is additionally associated with aggregate information like the sum of all leaf-entries indexed by that node. Our solution outperforms the state-of-the-art RkNN algorithms in terms of query execution times because it exploits advanced strategies for pruning index entries.
Hans-Peter Kriegel, Peer Kröger, Matthias Ren
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where SSDBM
Authors Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Andreas Züfle, Alexander Katzdobler
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