Uncertain Location Based Range Aggregates in a Multi-dimensional Space

Uncertain data are inherent in many applications such as environmental surveillance and quantitative economics research. Considerable research efforts have been put into the field of analysing uncertain data. In this paper, we study the problem of processing the uncertain location based range aggregate in a multi-dimensional space. We first formally introduce the problem, then propose a general filtering-and-verification framework to solve the problem. Two filtering techniques, named STF and PCR respectively, are proposed to significantly reduce the verification cost.