Probabilistic Skylines on Uncertain Data

Uncertain data are inherent in some important applications. Although a considerable amount of research has been dedicated to modeling uncertain data and answering some types of queries on uncertain data, how to conduct advanced analysis on uncertain data remains an open problem at large. In this paper, we tackle the problem of skyline analysis on uncertain data. We propose a novel probabilistic skyline model where an uncertain object may take a probability to be in the skyline, and a p-skyline contains all the objects whose skyline probabilities are at least p. Computing probabilistic skylines on large uncertain data sets is challenging. We develop two efficient algorithms. The bottom-up algorithm computes the skyline probabilities of some selected instances of uncertain objects, and uses those instances to prune other instances and uncertain objects effectively. The top-down algorithm recursively partitions the instances of uncertain objects into subsets, and prunes subsets and obje...

• Type: Conference
• Year: 2007
• Where: VLDB
• Authors: Jian Pei, Bin Jiang, Xuemin Lin, Yidong Yuan
• Keywords: Database, Probabilistic Skylines, Uncertain Data, Uncertain Objects, VLDB 2007