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.

• Type: Conference
• Year: 2009
• Where: SSDBM
• Authors: Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Andreas Züfle, Alexander Katzdobler
• Keywords: Database, Euclidean Spaces, MultiResolution Aggregate, Reverse K-nearest Neighbor, SSDBM 2009