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基双色子反近邻的查询在空间数据库领很有应用价值.在实际中,设施会要受到自身服务能力的限制.当需求快速增长时,那些处服务密集区的设施很可能不堪重负.研究了一种与双色子反近邻集合相关的查询,旨在找到最具潜力的候选位置来最大程度的提高整个区的服务质量.使用剪枝技术和空间索引技术,提出了时间复杂度为O(nlogn)的算法快速有效的完成这种查询.为了评价算法的效率,我们在真实数据集和合成数据集上做了实验,结果显示提出的算法十分优基本算法.“,”Bichromatic reverse nearest neighbor (BRNN) has great potential for real life applications and re-ceives 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 over-loading.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 algorithm using pruning tech-niques 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 solu-tion.