Abstract—Uncertain data are inherent in many applications such as environmental surveillance and quantitative economics research. Recently, 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 signficantly reduce the verification cost.

摘要--不确定数据库有很多固有应用，比如说环境监控和质量经济学研究。最后，在分析不确定数据库分析呈现了很多研究成果。本文，我们研究了在多维空间上的基于初始聚集本地不确定处理。我们首先形成问题介绍，然后提出了一个普通的过滤确认框架来解决这个问题。两个过滤技术 STF和PCR被提出很大地减少了确认代价。