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Skyline Computation with Noisy Comparisons
[chapter]
2020
Lecture Notes in Computer Science
Given a set of n points in a d-dimensional space, we seek to compute the skyline, i.e., those points that are not strictly dominated by any other point, using few comparisons between elements. We adopt the noisy comparison model [15] where comparisons fail with constant probability and confidence can be increased through independent repetitions of a comparison. In this model motivated by Crowdsourcing applications, Groz and Milo [18] show three bounds on the query complexity for the skyline
doi:10.1007/978-3-030-48966-3_22
fatcat:ezxphq7uyfctfdr5ibr56qtene