Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data

Abstract. Large amount of uncertain data is inherent in many novel and important applications such as sensor data analysis and mobile data management. A probabilistic threshold range aggregate (PTRA) query retrieves summarized information about the uncertain objects satisfying a range query, with respect to a given probability threshold. This paper
is the first one to address this important type of query. We develop a new index structure aU-tree and propose an exact querying algorithm based on aU-tree. For the pursue of efficiency, two techniques SingleSample and DoubleSample are developed. Both techniques provide approximate answers to a PTRA query with accuracy guarantee. Experimental study demonstrates the efficiency and effectiveness of our proposed methods.

摘要。大量的不确定性数据库有着很多新的和重要的应用，比如传感器信息分析和移动信息管理。关于不确定目档一个概率阈值聚集（PTRA）查询检索相关信息，期望给出一个概率阈值。本文首页说明和查询的重要性，我们开发了一个新的索引结构aU-tree 并且提出一个人精确的基于aU-tree查询算法。为了追求效率，开发了两个技术单抽样和双抽样。这两个技术提供了一个PTRA查询的精确渐近解。实验研究证明了我们提出的方法的效率和性能。