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Efficient algorithm for k representative regret minimization G-Skyline queries
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AI
DOI：10.1016/j.eswa.2025.130454.png)
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Abstract
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• A novel k representative regret minimization G-Skyline (kRMG) query is proposed. • The efficient algorithm PHP with a hierarchical pruning strategy is proposed. • PHP* proposes two novel improvement strategies to further enhance performance. • Extensive experimental results show that PHP and PHP* are efficient and reliable.
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