Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The Management of Probabilistic Data
IEEE Transactions on Knowledge and Data Engineering
Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and 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
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
Trio: a system for data, uncertainty, and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Streaming Algorithms for Robust, Real-Time Detection of DDoS Attacks
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
Continuous K-nearest neighbor queries for continuously moving points with updates
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Approximate NN queries on streams with guaranteed error/performance bounds
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
Probabilistic skylines on uncertain data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Query language support for incomplete information in the MayBMS system
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Monochromatic and bichromatic reverse skyline search over uncertain databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Ranking queries on uncertain data: a probabilistic threshold approach
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Orion 2.0: native support for 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
Conditioning probabilistic databases
Proceedings of the VLDB Endowment
Efficient search for the top-k probable nearest neighbors in uncertain databases
Proceedings of the VLDB Endowment
Cleaning uncertain data with quality guarantees
Proceedings of the VLDB Endowment
Access control over uncertain data
Proceedings of the VLDB Endowment
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
The VLDB Journal — The International Journal on Very Large Data Bases
Probabilistic threshold k nearest neighbor queries over moving objects in symbolic indoor space
Proceedings of the 13th International Conference on Extending Database Technology
Querying and cleaning uncertain data
QuaCon'09 Proceedings of the 1st international conference on Quality of context
Skyline query processing for uncertain data
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Selective data acquisition for probabilistic K-NN query
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Ranking continuous probabilistic datasets
Proceedings of the VLDB Endowment
k-nearest neighbors in uncertain graphs
Proceedings of the VLDB Endowment
A unified approach to ranking in probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
Probabilistic time consistent queries over moving objects
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
k-selection query over uncertain data
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
MUD: Mapping-based query processing for high-dimensional uncertain data
Information Sciences: an International Journal
Nearest-neighbor searching under uncertainty
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
A filter-based protocol for continuous queries over imprecise location data
Proceedings of the 21st ACM international conference on Information and knowledge management
Probabilistic top-k dominating queries in uncertain databases
Information Sciences: an International Journal
An RFID and particle filter-based indoor spatial query evaluation system
Proceedings of the 16th International Conference on Extending Database Technology
Nearest neighbor searching under uncertainty II
Proceedings of the 32nd symposium on Principles of database systems
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In emerging applications such as location-based services, sensor monitoring and biological management systems, the values of the database items are naturally imprecise. For these uncertain databases, an important query is the Probabilistic k-Nearest-Neighbor Query (k-PNN), which computes the probabilities of sets of k objects for being the closest to a given query point. The evaluation of this query can be both computationally- and I/O-expensive, since there is an exponentially large number of k object-sets, and numerical integration is required. Often a user may not be concerned about the exact probability values. For example, he may only need answers that have sufficiently high confidence. We thus propose the Probabilistic Threshold k-Nearest-Neighbor Query (T-k-PNN), which returns sets of k objects that satisfy the query with probabilities higher than some threshold T. Three steps are proposed to handle this query efficiently. In the first stage, objects that cannot constitute an answer are filtered with the aid of a spatial index. The second step, called probabilistic candidate selection, significantly prunes a number of candidate sets to be examined. The remaining sets are sent for verification, which derives the lower and upper bounds of answer probabilities, so that a candidate set can be quickly decided on whether it should be included in the answer. We also examine spatially-efficient data structures that support these methods. Our solution can be applied to uncertain data with arbitrary probability density functions. We have also performed extensive experiments to examine the effectiveness of our methods.