Efficient computation of range aggregates against uncertain location-based queries

Publication Type:
Journal Article
IEEE Transactions on Knowledge and Data Engineering, 2012, 24 (7), pp. 1244 - 1258
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2013005448OK.pdf1.73 MB
Adobe PDF
In many applications, including location-based services, queries may not be precise. In this paper, we study the problem of efficiently computing range aggregates in a multidimensional space when the query location is uncertain. Specifically, for a query point Q whose location is uncertain and a set S of points in a multidimensional space, we want to calculate the aggregate (e.g., count, average and sum) over the subset S′ of S such that for each p ∈ S′, Q has at least probability θ within the distance \gamma to p. We propose novel, efficient techniques to solve the problem following the filtering-and-verification paradigm. In particular, two novel filtering techniques are proposed to effectively and efficiently remove data points from verification. Our comprehensive experiments based on both real and synthetic data demonstrate the efficiency and scalability of our techniques. © 2012 IEEE.
Please use this identifier to cite or link to this item: