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- W2600377448 abstract "Skyline queries continue to attract attentions since the skyline operator was first proposed in 2001. In this paper, we propose a fast skyline computation approach, called HashSkyline, with two unique features: First, HashSkyline minimizes the pre-processing cost to O(n) by effectively utilizing the characteristics of correlated datasets. Second, HashSkyline capitalizes on a hash cell based mechanism to learn the level of correlation among the data points in a given dataset at low processing cost, allowing early detection of anti-correlated datasets at early stage to avoid uninteresting and yet high cost of computing skylines on anti-correlated datasets." @default.
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- W2600377448 date "2016-10-17" @default.
- W2600377448 modified "2023-10-16" @default.
- W2600377448 title "Exploring correlation for fast skyline computation" @default.
- W2600377448 cites W1972541019 @default.
- W2600377448 doi "https://doi.org/10.1145/3007818.3007843" @default.
- W2600377448 hasPublicationYear "2016" @default.
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