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- W2807869082 abstract "Skyline query processing has recently received a lot of attention in the big data analysis community. However, in most real applications, the skyline result can not satisfy the needs of users. In this paper, we propose a novel type of skyEXP query to more efficiently analyze and explore the data. The skyEXP query on the subspace V divides the input data M into w separate subsets SE1 (M, V),…, SEw (M, V) such that an object p belongs to SEi (M, V) if it is not dominated by any other objects on V except for those in SE1 (M, V),…, SEi−1(M, V) where i ∈ [1, w]. In order to fast implement the proposed query over big data, an efficient parallel algorithm SQMRM (the SkyEXP Query using Map-Reduce Model) which utilizes the map-reduce framework is presented. Detailed theoretical analyses and extensive experiments demonstrate that our SQMRM algorithm is both efficient and effective." @default.
- W2807869082 created "2018-06-21" @default.
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- W2807869082 date "2018-01-01" @default.
- W2807869082 modified "2023-09-27" @default.
- W2807869082 title "Efficient Processing of the SkyEXP Query Over Big Data" @default.
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- W2807869082 doi "https://doi.org/10.1007/978-981-13-0893-2_40" @default.
- W2807869082 hasPublicationYear "2018" @default.
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