Stochastic skyline operator

— In many applications involving the multiple criteria optimal decision making, users may often want to make a personal trade-off among all optimal solutions. As a key feature, the skyline in a multi-dimensional space provides the minimum set of candidates for such purposes by removing all points not preferred by any (monotonic) utility/scoring functions; that is, the skyline removes all objects not preferred by any user no mater how their preferences vary. Driven by many applications with uncertain data, the probabilistic skyline model is proposed to retrieve uncertain objects based on skyline probabilities. Nevertheless, skyline probabilities cannot capture the preferences of monotonic utility functions. Motivated by this, in this paper we propose a novel skyline operator, namely stochastic skyline. In the light of the expected utility principle, stochastic skyline guarantees to provide the minimum set of candidates for the optimal solutions over all possible monotonic multiplicati...

• Type: Journal
• Year: 2011
• Where: ICDE
• Authors: Xuemin Lin, Ying Zhang, Wenjie Zhang, Muhammad Aamir Cheema
• Keywords: Database, ICDE 2011, Probabilistic Skyline, Skyline Probabilities, Stochastic Skyline