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- W2098508740 abstract "Query all skyline points in large high-dimension dataset is quite challenging and its space and computation overhead are massive. This paper presents QBHSQ, a novel Quad-tree based algorithm for skyline query in large high-dimension dataset. QBHSQ utilizes a partial dimension subset to partition dataset on high dimensional space by means of the configuration characters of quad-tree. Since amount of domination checking operators among non-domination sub-datasets can be reduced and large numbers of data points in high dimensional space are deleted while constructing tree, QBHSQ contributes to a better computation and space performance than traditional ones. Extensive experiments demonstrate the efficiency and the scalability of proposed algorithm." @default.
- W2098508740 created "2016-06-24" @default.
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- W2098508740 date "2009-01-01" @default.
- W2098508740 modified "2023-09-27" @default.
- W2098508740 title "QBHSQ: A Quad-tree Based Algorithm for High-dimension Skyline Query" @default.
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- W2098508740 doi "https://doi.org/10.1109/iita.2009.113" @default.
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