Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and Data Engineering
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
The Gauss-Tree: Efficient Object Identification in Databases of Probabilistic Feature Vectors
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Range search on multidimensional uncertain data
ACM Transactions on Database Systems (TODS)
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Probabilistic ranked queries in uncertain databases
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Efficient search for the top-k probable nearest neighbors in uncertain databases
Proceedings of the VLDB Endowment
Efficient Processing of Top-k Queries in Uncertain Databases with x-Relations
IEEE Transactions on Knowledge and Data Engineering
Efficiently Answering Probabilistic Threshold Top-k Queries on Uncertain Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Spatial Range Querying for Gaussian-Based Imprecise Query Objects
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Flexible query answering using distance-based fuzzy relations
TARSKI'02-05 Proceedings of the 2006 international conference on Theory and Applications of Relational Structures as Knowledge Instruments - Volume 2
Fuzzy query translation for relational database systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Top-K probabilistic closest pairs query in uncertain spatial databases
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Evaluating probabilistic spatial-range closest pairs queries over uncertain objects
WAIM'11 Proceedings of the 12th international conference on Web-age information management
Efficient fuzzy ranking queries in uncertain databases
Applied Intelligence
| Hi-index | 0.00 |
Recently, many application domains, such as sensor network monitoring and Location-Based Service, raise the issue of uncertain data management. Uncertain objects, a kind of uncertain data, have some uncertain attributes whose values are ranges instead of points. In this paper, we study a new kind of top-k queries, Probabilistic Fuzzy Top-k queries (PF-Topk queries) which can return k results from uncertain objects for fuzzy query conditions. We formally define the problem of PF-Topk query and present a framework for answering this kind of queries. We propose an exact algorithm, Envelope Planes of Membership Function (EPMF) algorithm based on the upper and lower bounding functions, which answers fuzzy top-k queries over uncertain objects in high-dimensional query space efficiently. We also propose an approximate algorithm which improves efficiency while ensuring high precision by setting a proper value of parameter. To reduce the search space, a pruning method is proposed to safely prune some objects before querying. The effectiveness and efficiency of our algorithms is demonstrated by the theoretical analysis and experiments with synthetic and real datasets.