New upper bounds for neighbor searching
Information and Control
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Aggregate Processing of Planar Points
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Mining preferences from superior and inferior examples
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
On domination game analysis for microeconomic data mining
ACM Transactions on Knowledge Discovery from Data (TKDD)
Processing spatial skyline queries in both vector spaces and spatial network databases
ACM Transactions on Database Systems (TODS)
Proceedings of the VLDB Endowment
Efficient mining of skyline objects in subspaces over data streams
Knowledge and Information Systems
Skyline-sensitive joins with LR-pruning
Proceedings of the 15th International Conference on Extending Database Technology
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Dominance analysis is important in many multi-criteria decision making applications. Most previous works assume that the price of a service is given and study how to select "best" services according to multiple given attributes including attribute Price. In this paper, we propose an interesting data mining problem, finding competitive price, which has not been studied before. Given a set of existing services, for a new service, we want to find a price of the new service such that the new service is not worse than any existing services. The price found refers to a competitive price. We propose a spatial approach which makes use of some spatial properties and thus runs efficiently. Finally, we conducted experiments to show the efficiency of our proposed method.