Queries with segments in Voronoi diagrams
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
K-Nearest Neighbor Search for Moving Query Point
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Nearest neighbor queries in road networks
GIS '03 Proceedings of the 11th ACM international symposium on Advances in geographic information systems
Continuous K-Nearest Neighbor Search for Moving Objects
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Search on transportation network for location-based service
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Continuous nearest neighbor search
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
The TPR*-tree: an optimized spatio-temporal access method for predictive queries
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Voronoi-based K nearest neighbor search for spatial network databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Stepwise optimization method for k-CNN search for location-based service
SOFSEM'05 Proceedings of the 31st international conference on Theory and Practice of Computer Science
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Continuous K nearest neighbor (CkNN) queries under mobile environment are defined as the k nearest neighbors search for a query object at a serial query time, and all the query object and the target objects are moving. In this paper, we propose method to solve this problem, focusing on finding out the relations between the continuous queries, and proposing decision method for relative moving trend among moving objects. Our experiments show that our approach outperforms the original straightforward method, specially when the query interval is small.