Supporting valid-time indeterminacy
ACM Transactions on Database Systems (TODS)
IEEE Transactions on Computers
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Main Memory Evaluation of Monitoring Queries Over Moving Objects
Distributed and Parallel Databases
Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and Data Engineering
Change Tolerant Indexing for Constantly Evolving Data
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
SEA-CNN: Scalable Processing of Continuous K-Nearest Neighbor Queries in Spatio-temporal Databases
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Indexing multi-dimensional uncertain data with arbitrary probability density functions
VLDB '05 Proceedings of the 31st international conference on Very large data bases
The Gauss-Tree: Efficient Object Identification in Databases of Probabilistic Feature Vectors
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
ULDBs: databases with uncertainty and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficient query evaluation on probabilistic databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
MCDB: a monte carlo approach to managing uncertain data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Probabilistic Group Nearest Neighbor Queries in Uncertain Databases
IEEE Transactions on Knowledge and Data Engineering
Efficient search for the top-k probable nearest neighbors in uncertain databases
Proceedings of the VLDB Endowment
Evaluating probability threshold k-nearest-neighbor queries over uncertain data
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Efficient Processing of Top-k Queries in Uncertain Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Probabilistic Verifiers: Evaluating Constrained Nearest-Neighbor Queries over Uncertain Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Probabilistic nearest-neighbor query on uncertain objects
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
CkNN query processing over moving objects with uncertain speeds in road networks
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Evaluating continuous probabilistic queries over imprecise sensor data
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Evaluating trajectory queries over imprecise location data
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Probabilistic filters: A stream protocol for continuous probabilistic queries
Information Systems
A filter-based protocol for continuous queries over imprecise location data
Proceedings of the 21st ACM international conference on Information and knowledge management
Report on the first workshop on innovative querying of streams
ACM SIGMOD Record
UV-diagram: a voronoi diagram for uncertain spatial databases
The VLDB Journal — The International Journal on Very Large Data Bases
Efficiently Producing the K Nearest Neighbors in the Skyline on Vertically Partitioned Tables
International Journal of Information Retrieval Research
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In several emerging and important applications, such as location-based services, sensor monitoring and biological databases, the values of the data items are inherently imprecise. A useful query class for these data is the Probabilistic Nearest-Neighbor Query (PNN), which yields the IDs of objects for being the closest neighbor of a query point, together with the objects' probability values. Previous studies showed that this query takes a long time to evaluate. To address this problem, we propose the Constrained Nearest-Neighbor Query (C-PNN), which returns the IDs of objects whose probabilities are higher than some threshold, with a given error bound in the answers. We show that the C-PNN can be answered efficiently with verifiers. These are methods that derive the lower and upper bounds of answer probabilities, so that an object can be quickly decided on whether it should be included in the answer. We design five verifiers, which can be used on uncertain data with arbitrary probability density functions. We further develop a partial evaluation technique, so that a user can obtain some answers quickly, without waiting for the whole query evaluation process to be completed (which may incur a high response time). In addition, we examine the maintenance of a long-standing, or continuous C-PNN query. This query requires any update to be applied to the result immediately, in order to reflect the changes to the database values (e.g., due to the change of the location of a moving object). We design an incremental update method based on previous query answers, in order to reduce the amount of I/O and CPU cost in maintaining the correctness of the answers to such a query. Performance evaluation on realistic datasets show that our methods are capable of yielding timely and accurate results.