On the representation and querying of sets of possible worlds
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
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
Multidimensional binary search trees used for associative searching
Communications of the ACM
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and Data Engineering
Trio: a system for data, uncertainty, and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Reverse kNN search in arbitrary dimensionality
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Probabilistic skylines on uncertain data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Orion 2.0: native support for uncertain data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Efficient search for the top-k probable nearest neighbors in uncertain databases
Proceedings of the VLDB Endowment
Probabilistic Inverse Ranking Queries over Uncertain Data
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
Probabilistic Verifiers: Evaluating Constrained Nearest-Neighbor Queries over Uncertain Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Semantics of Ranking Queries for Probabilistic Data and Expected Ranks
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Efficient processing of probabilistic reverse nearest neighbor queries over uncertain data
The VLDB Journal — The International Journal on Very Large Data Bases
Consensus answers for queries over probabilistic databases
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A unified approach to ranking in probabilistic databases
Proceedings of the VLDB Endowment
Probabilistic Reverse Nearest Neighbor Queries on Uncertain Data
IEEE Transactions on Knowledge and Data Engineering
Boosting spatial pruning: on optimal pruning of MBRs
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Scalable Probabilistic Similarity Ranking in Uncertain Databases
IEEE Transactions on Knowledge and Data Engineering
Ranking continuous probabilistic datasets
Proceedings of the VLDB Endowment
A novel probabilistic pruning approach to speed up similarity queries in uncertain databases
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Probabilistic range monitoring of streaming uncertain positions in geosocial networks
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Efficiently processing snapshot and continuous reverse k nearest neighbors queries
The VLDB Journal — The International Journal on Very Large Data Bases
Finding top k most influential spatial facilities over uncertain objects
Proceedings of the 21st ACM international conference on Information and knowledge management
Causality and responsibility: probabilistic queries revisited in uncertain databases
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Mining co-locations under uncertainty
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
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Given a query object q, a reverse nearest neighbor (RNN) query in a common certain database returns the objects having q as their nearest neighbor. A new challenge for databases is dealing with uncertain objects. In this paper we consider probabilistic reverse nearest neighbor (PRNN) queries, which return the uncertain objects having the query object as nearest neighbor with a sufficiently high probability. We propose an algorithm for efficiently answering PRNN queries using new pruning mechanisms taking distance dependencies into account. We compare our algorithm to state-of-the-art approaches recently proposed. Our experimental evaluation shows that our approach is able to significantly outperform previous approaches. In addition, we show how our approach can easily be extended to PRkNN (where k 1) query processing for which there is currently no efficient solution.