摘要
不确定数据在一些重要应用领域中是固有存在的,如传感器网络和移动物体追踪。在不确定数据上使用传统的查询方法会使查询结果出现偏差,不能满足用户的需求。因此,基于不确定数据的查询处理受到了越来越多的关注。与在确定数据上查询不同,不确定数据上的研究工作将概率引入到数据模型中来衡量不确定对象成为结果集中元素的可能性。由于问题定义和数据模型的不同,不确定数据上的查询类型也多种多样。从问题定义、数据模型、剪枝策略和算法等角度,对基于不确定数据的范围查询、top-k查询以及skyline查询进行了介绍。
Uncertain data is inherent in some important application fields, such as sensor networks and mobile object tracking. Using traditional querying methods on uncertain data will bias the answer set, and hence cannot satisfy users＇ needs. Therefore, query, processing based on uncertain data has attracted more and more attention. Different from queries on certain data, research work on uncertain data introduce probability into data model to measure the likeness of an uncertain object as one element of the answer set. Due to different problem definitions and data models, query types differentiate from each other greatly. This survey introduced range queries, top-k queries and skyline queries based on uncertain data from the views of problem definitions, data models, pruning strategies and algorithms.
出处
《计算机应用》
CSCD
北大核心
2008年第11期2729-2731,2744,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(60603045)
国家863计划项目(2007AA01Z153)
