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Subspace l-SkyRex query processing has recently received a lot of attention in database community. Given a set of multidimensional objects, l-SkyRex query on Subspace V finds the objects that are dominated by at most l objects on this subspace. In multi-user environments, skyline analysis systems need the capabilities to optimize multiple subspace l-SkyRex queries simultaneously. Therefore, for this purpose, we also propose AOMSSQ (Algorithm for Optimizing Multiple Subspace l-SkyRex Queries), the first efficient sound and complete algorithm to optimize multiple subspace l-SkyRex queries in multi-user environments. Finally, we discuss two interesting variations of subspace l-SkyRex query, i.e., global constraint subspace l-SkyRex query and local constraint subspace l-SkyRex query, which are meaningful in practice, and show how our solutions can be applied for their efficient processing. Detailed theoretical analyses and extensive experiments that demonstrate our algorithms are both efficient and effective. |
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Keywords:database; l-SkyRex query; subspace; query optimization |
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