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Top-k Most Incremental Location Selection with Capacity Constraint

机译:具有容量限制的Top-k最大增量位置选择

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Bichromatic reverse nearest neighbor (BRNN) based query uses the number of reverse nearest customers to model the influence of a facility location. The query has great potential for real life applications and receives considerable attentions from spatial database studies. In real world, facilities are inevitably constrained by designed capacities. When the needs of service increase, facilities in those booming areas may suffer from overloading. In this paper, we study a new kind of BRNN related query. It aims at finding most promising candidate locations to increase the overall service quality. To efficiently answer the query, we propose an O(n log n) algorithm using pruning techniques and spatial indices. To evaluate the efficiency of proposed algorithm, we conduct extensive experiments on both real and synthetic datasets. The results show our algorithm has superior performance over the basic solution.
机译:基于双色反向最近邻(BRNN)的查询使用反向最近客户的数量来模拟设施位置的影响。该查询对于现实生活中的应用具有巨大的潜力,并且受到空间数据库研究的极大关注。在现实世界中,设施不可避免地受到设计能力的限制。当服务需求增加时,那些繁荣地区的设施可能会遭受超负荷的困扰。在本文中,我们研究了一种新型的BRNN相关查询。它旨在寻找最有希望的候选地点,以提高整体服务质量。为了有效地回答查询,我们提出了使用修剪技术和空间索引的O(n log n)算法。为了评估所提出算法的效率,我们在真实和合成数据集上进行了广泛的实验。结果表明,我们的算法具有优于基本解决方案的性能。

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