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• W2067304854 abstract "We introduce the Haar <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>+</sup> tree: a refined, wavelet-inspired data structure for synopsis construction. The advantages of this structure are twofold: First, it achieves higher synopsis quality at the task of summarizing data sets with sharp discontinuities than state-of-the-art histogram and Haar wavelet techniques. Second, thanks to its search space delimitation capacity, Haar <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>+</sup> synopsis construction operates in time linear to the size of the data set for any monotonic distributive error metric. Through experimentation, we demonstrate the superiority of Haar <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>+</sup> synopses over histogram and Haar wavelet methods in both construction time and achieved quality for representative error metrics." @default.
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• W2067304854 date "2007-04-01" @default.
• W2067304854 modified "2023-10-14" @default.
• W2067304854 title "The Haar+ Tree: A Refined Synopsis Data Structure" @default.
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• W2067304854 doi "https://doi.org/10.1109/icde.2007.367889" @default.
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