The most-likely skyline problem for stochastic points

Akash Agrawal; Yuan Li; Jie Xue; Ravi Janardan

The most-likely skyline problem for stochastic points

Akash Agrawal, Yuan Li, Jie Xue, Ravi Janardan

Computer Science and Engineering

Research output: Contribution to conference › Paper › peer-review

4 Scopus citations

Abstract

For a set O of n points in R^d, the skyline consists of the subset of all points of O where no point is dominated by any other point of O. Suppose that each point o_i ∈ O has an associated probability of existence p_i ∈ (0, 1]. The problem of computing the skyline with the maximum probability of occurrence is considered. It is shown that in R^d, d ≥ 3, the problem is NP-hard and that the desired skyline cannot even be well-approximated in polynomial-time unless P = NP. In R², an optimal O(n log n)-time and O(n)-space algorithm is given.

Original language	English (US)
Pages	78-83
Number of pages	6
State	Published - 2017
Event	29th Canadian Conference on Computational Geometry, CCCG 2017 - Ottawa, Canada Duration: Jul 26 2017 → Jul 28 2017

Conference

Conference	29th Canadian Conference on Computational Geometry, CCCG 2017
Country/Territory	Canada
City	Ottawa
Period	7/26/17 → 7/28/17

Bibliographical note

Funding Information:
The research of the first author was supported, in part, by a Doctoral Dissertation Fellowship from the Graduate School of the University of Minnesota.

Publisher Copyright:
Compilation copyright © 2017 Michiel Smid Copyright of individual papers retained by authors.All right reserved.

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abstract = "For a set O of n points in Rd, the skyline consists of the subset of all points of O where no point is dominated by any other point of O. Suppose that each point oi ∈ O has an associated probability of existence pi ∈ (0, 1]. The problem of computing the skyline with the maximum probability of occurrence is considered. It is shown that in Rd, d ≥ 3, the problem is NP-hard and that the desired skyline cannot even be well-approximated in polynomial-time unless P = NP. In R2, an optimal O(n log n)-time and O(n)-space algorithm is given.",

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AB - For a set O of n points in Rd, the skyline consists of the subset of all points of O where no point is dominated by any other point of O. Suppose that each point oi ∈ O has an associated probability of existence pi ∈ (0, 1]. The problem of computing the skyline with the maximum probability of occurrence is considered. It is shown that in Rd, d ≥ 3, the problem is NP-hard and that the desired skyline cannot even be well-approximated in polynomial-time unless P = NP. In R2, an optimal O(n log n)-time and O(n)-space algorithm is given.

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The most-likely skyline problem for stochastic points

Abstract

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