Probabilistic Skyline Operator over Sliding Windows 粗译

Abstract—Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of efficient processing of continuous skyline queries over sliding windows on uncertain data elements regarding given probability thresholds. We first characterize what kind of elements we need to keep in our query computation. Then we show the size of dynamically maintained candidate set and the size of skyline. We develop novel, efficient techniques to process a continuous, probabilistic skyline query. Finally, we extend our techniques to the applications where multiple probability thresholds are given or we want to retrieve “top-k” skyline data objects. Our extensive experiments demonstrate that the proposed techniques are very efficient and handle a high-speed data stream in real time.

在滑动窗口下的概率性skyline操作

摘要-skyline计算有很多应用包括复合条件决策。在本文中，我们研究了关于在给定阈值条件下的不确定数据元素下的滑动窗口下的持继性性skyline有效处理操作问题。我们首先将哪一种元素需要进行计算问题做一个定性化描述，然后我们描述了动态维护侯选集和skyline的大小。我们开发了一个新的，有效的算法用来处理持续的，概率的skyline问题。最后，我们延伸了我们的技术应用在给定多重概率阈值或者尝试获得top-k skyline数据对象。我们的大量实验证明这种技术是什么有效的并且能够处理高速的实时数据流。