Range Queries on Uncertain Data
Abstract
Given a set of uncertain points on the real line, each represented by its one-dimensional probability density function, we consider the problem of building data structures on to answer range queries of the following three types for any query interval : (1) top- query: find the point in that lies in with the highest probability, (2) top- query: given any integer as part of the query, return the points in that lie in with the highest probabilities, and (3) threshold query: given any threshold as part of the query, return all points of that lie in with probabilities at least . We present data structures for these range queries with linear or nearly linear space and efficient query time.
Cite
@article{arxiv.1501.02309,
title = {Range Queries on Uncertain Data},
author = {Jian Li and Haitao Wang},
journal= {arXiv preprint arXiv:1501.02309},
year = {2015}
}
Comments
26 pages. A preliminary version of this paper appeared in ISAAC 2014. In this full version, we also present solutions to the most general case of the problem (i.e., the histogram bounded case), which were left as open problems in the preliminary version