首页    期刊浏览 2024年12月05日 星期四
登录注册

文章基本信息

  • 标题:Probabilistic Skyline Queries over Uncertain Moving Objects
  • 其他标题:Probabilistic Skyline Queries over Uncertain Moving Objects
  • 作者:Ding, Xiaofeng ; Jin, Hai ; Xu, Hui
  • 期刊名称:COMPUTING AND INFORMATICS
  • 印刷版ISSN:1335-9150
  • 出版年度:2013
  • 卷号:32
  • 期号:5
  • 页码:987-1012
  • 语种:English
  • 出版社:COMPUTING AND INFORMATICS
  • 摘要:Data uncertainty inherently exists in a large number of applications due to factors such as limitations of measuring equipments, update delay, and network bandwidth. Recently, modeling and querying uncertain data have attracted considerable attention from the database community. However, how to perform advanced analysis on uncertain data remains an interesting question. In this paper, we focus on the execution of skyline computation over uncertain moving objects. We propose a novel probabilistic skyline model where an uncertain object may take a probability to be in the skyline at a certain time point, therefore a p-t-skyline contains those moving objects whose skyline probabilities are at least p at time point t. Computing probabilistic skyline over a large number of uncertain moving objects is a daunting task in practice. In order to efficiently compute the probabilistic skyline query, we propose a discrete-and-conquer strategy, which follows the sampling-bounding-pruning-refining procedure. To further reduce the skyline computation cost, we propose an enhanced framework that is based on a multi-dimensional indexing structure combined with the discrete-and-conquer strategy. Through extensive experiments with synthetic datasets, we show that the framework can efficiently support skyline queries over uncertain moving object and is scalable on large data sets.
  • 关键词:Mobile computing; probabilistic skyline query; uncertain data;68-P10
Loading...
联系我们|关于我们|网站声明
国家哲学社会科学文献中心版权所有