Sep 7, 2015 · We envision applications in facility location, sensor networks, and other scenarios where a connection between two entities becomes less likely ...
Aug 9, 2016 · We present a fast, sublinear-time query algorithm to sample probabilistic neighborhoods from planar point sets.
Abstract. The probability that two spatial objects establish some kind of mutual connection often depends on their proximity. To formalize this.
Querying Probabilistic Neighborhoods in Spatial Data Sets Efficiently ; Identifikator, ISBN: 978-3-319-44542-7. ISSN: 0302-9743 KITopen-ID: 1000060099.
Abstract—We study the problem of answering spatial queries in databases where objects exist with some uncertainty and they are.
In this paper, we address the problem how to perform spatial database operations in the presence of uncertainty. We first discuss a probabilistic spatial data ...
Uncertain data are inherent in some important applications, such as environmental surveillance, market analysis, and quantitative economics research.
The goal is to preprocess the input set into a data structure, such that given a query range, one can efficiently report all input objects intersecting the ...
Abstract. Spatial databases typically assume that the positional at- tributes of spatial objects are precisely known. In practice, however, they.
Missing: Neighborhoods | Show results with:Neighborhoods
In this paper, we propose a Probabilistic Maximum Range-Sum (PMaxRS) query over uncertain spatial objects, which obtains a set γ* of rectangles such that the ...