The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Influence sets based on reverse nearest neighbor queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Progressive approximate aggregate queries with a multi-resolution tree structure
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
An Index Structure for Efficient Reverse Nearest Neighbor Queries
Proceedings of the 17th International Conference on Data Engineering
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Efficient OLAP Operations in Spatial Data Warehouses
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
High dimensional reverse nearest neighbor queries
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Efficient reverse k-nearest neighbor search in arbitrary metric spaces
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Reverse Nearest Neighbor Search in Metric Spaces
IEEE Transactions on Knowledge and Data Engineering
Approximate reverse k-nearest neighbor queries in general metric spaces
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Reverse kNN search in arbitrary dimensionality
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficient RkNN retrieval with arbitrary non-metric similarity measures
Proceedings of the VLDB Endowment
Reverse-k-Nearest-Neighbor join processing
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
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We propose an original solution for the general reverse k -nearest neighbor (Rk NN) search problem in Euclidean spaces. Compared to the limitations of existing methods for the RkNN search, our approach works on top of Multi-Resolution Aggregate (MRA) versions of any index structures for multidimensional 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.