Evaluating probability threshold k-nearest-neighbor queries over uncertain data
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient join processing on uncertain data streams
Proceedings of the 18th ACM conference on Information and knowledge management
Reverse skyline search in uncertain databases
ACM Transactions on Database Systems (TODS)
Probabilistic inverse ranking queries in uncertain databases
The VLDB Journal — The International Journal on Very Large Data Bases
Uncertain distance-based range queries over uncertain moving objects
Journal of Computer Science and Technology
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
Aggregate farthest-neighbor queries over spatial data
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications: Part II
Probabilistic time consistent queries over moving objects
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
Efficient processing of probabilistic set-containment queries on uncertain set-valued data
Information Sciences: an International Journal
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
Probabilistic Voronoi diagrams for probabilistic moving nearest neighbor queries
Data & Knowledge Engineering
UV-diagram: a voronoi diagram for uncertain spatial databases
The VLDB Journal — The International Journal on Very Large Data Bases
Reverse top-k group nearest neighbor search
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Aggregate nearest neighbor queries in uncertain graphs
World Wide Web
Hi-index | 0.00 |
The importance of query processing over uncertain data has recently arisen due to its wide usage in many real-world applications. In the context of uncertain databases, previous work have studied many query types such as nearest neighbor query, range query, top-$k$ query, skyline query, and similarity join. In this paper, we focus on another important query, namely probabilistic group nearest neighbor query (PGNN), in the uncertain database, which also has many applications. Specifically, given a set, Q, of query points, a PGNN query retrieves data objects that minimize the aggregate distance (e.g. sum, min, and max) to query set Q. Due to the inherent uncertainty of data objects, previous techniques to answer group nearest neighbor query (GNN) cannot be directly applied to our PGNN problem. Motivated by this, we propose effective pruning methods, namely spatial pruning and probabilistic pruning, to reduce the PGNN search space, which can be seamlessly integrated into our PGNN query procedure. Extensive experiments have demonstrated the efficiency and effectiveness of our proposed approach, in terms of the wall clock time and the speed-up ratio against linear scan.