Approximate closest-point queries in high dimensions
Information Processing Letters
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Approximate nearest neighbor queries in fixed dimensions
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
Spatial databases with application to GIS
Spatial databases with application to GIS
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Modeling and Querying Moving Objects
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Approximate Algorithms for Distance-Based Queries in High-Dimensional Data Spaces Using R-Trees
ADBIS '02 Proceedings of the 6th East European Conference on Advances in Databases and Information Systems
K-Nearest Neighbor Search for Moving Query Point
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
On Approximate Algorithms for Distance-Based Queries using R-trees
The Computer Journal
K nearest neighbor search in navigation systems
Mobile Information Systems
Continuous nearest neighbor search
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Query processing in spatial network databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Computational Geometry: Algorithms and Applications
Computational Geometry: Algorithms and Applications
High Performance Parallel Database Processing and Grid Databases
High Performance Parallel Database Processing and Grid Databases
Improving the space cost of k-NN search in metric spaces by using distance estimators
Multimedia Tools and Applications
The Effect of Corners on the Complexity of Approximate Range Searching
Discrete & Computational Geometry
Approximate Evaluation of Range Nearest Neighbor Queries with Quality Guarantee
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Approximate range searching: The absolute model
Computational Geometry: Theory and Applications
Introducing mobile devices into Grid systems: a survey
International Journal of Web and Grid Services
Voronoi-based range and continuous range query processing in mobile databases
Journal of Computer and System Sciences
Mobile Information Systems
Optimizing the performance and robustness of type-2 fuzzy group nearest-neighbor queries
Mobile Information Systems
International Journal of Data Warehousing and Mining
Efficient Monitoring of Moving Mobile Device Range Queries using Dynamic Safe Regions
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
Hi-index | 0.00 |
For many years, spatial range search has been applied to computational geometry and multimedia problems to find interest objects within a given radius. Range search query has traditionally been used to return all objects within a given radius. However, having all objects is not necessary, especially when there are already enough objects closer to the query point. Furthermore, expanding the radius may give users better results, especially when there are a lot of objects just outside the search boundary. Therefore, in this paper, we focus on approximate range search, where the query results are approximate, rather than exact. We propose approximate static range search (ARS) which combines two approaches, namely (i) lowerbound approximate range search, and (ii) upperbound approximate range search. Using ARS, we are able to deliver a better performance, together with low false hit and reasonable false miss. We also extend ARS in the context of a continuous query setting, in which the query moves. This is particularly important in spatial databases as a mobile user who invokes the query is moving. In terms of continuous range search, the intention is to find split points--the locations where the query results will be updated. Accordingly, we propose two methods for approximate continuous range search, namely (i) range search minimization, and (ii) split points minimization. Our performance evaluation which compares our methods with the traditional continuous range search shows that our methods considerably reduce the number of split points, thereby improving overall performance.