Probabilistic Skyline Operator over Sliding Windows

Publisher:
IEEE
Publication Type:
Conference Proceeding
Citation:
IEEE 25th International Conference on Data Engineering, 2009, pp. 1060 - 1071
Issue Date:
2009-01
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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.
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