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2008

Sliding-window top-k queries on uncertain streams

9 years 9 months ago
Sliding-window top-k queries on uncertain streams
Query processing on uncertain data streams has attracted a lot of attentions lately, due to the imprecise nature in the data generated from a variety of streaming applications, such as readings from a sensor network. However, all of the existing works on uncertain data streams study unbounded streams. This paper takes the first step towards the important and challenging problem of answering sliding-window queries on uncertain data streams, with a focus on arguably one of the most important types of queries--top-k queries. The challenge of answering sliding-window top-k queries on uncertain data streams stems from the strict space and time requirements of processing both arriving and expiring tuples in high-speed streams, combined with the difficulty of coping with the exponential blowup in the number of possible worlds induced by the uncertain data model. In this paper, we design a unified framework for processing sliding-window top-k queries on uncertain streams. We show that all the...
Cheqing Jin, Ke Yi, Lei Chen 0002, Jeffrey Xu Yu,
Added 28 Dec 2010
Updated 28 Dec 2010
Type Journal
Year 2008
Where PVLDB
Authors Cheqing Jin, Ke Yi, Lei Chen 0002, Jeffrey Xu Yu, Xuemin Lin
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