This paper is devoted to the investigation of the evaluation and query algorithm problem for the influence of spatial location based on RkNN (reverse k nearest neighbor). On the one hand, an object can make contribution to multiple locations. However, for the existing measures for evaluating the influence of spatial location, an object only makes contribution to one location, and its influence is usually measured by the number of spatial objects in the region. In this case, a new measure for evaluating the influence of spatial location based on the RkNN is proposed. Since the weight of the contribution is determined by the distance between the object and the location, the influence weight definition is given, which meets the actual applications. On the other hand, a query algorithm for the influence of spatial location is introduced based on the proposed measure. Firstly, an algorithm named INCH (INtersection’s Convex Hull) is applied to get candidate regions, where all objects are candidates. Then, kNN and Range-k are used to refine results. Then, according to the proposed measure, the weights of objects in RkNN results are computed, and the influence of the location is accumulated. The experimental results on the real data show that the optimized algorithms outperform the basic algorithm on efficiency. In addition, in order to provide the best customer service in the location problem and make the best use of all infrastructures, a location algorithm with the query is presented based on RkNN. The influence of each facility is calculated in the location program and the equilibrium coefficient is used to evaluate the reasonability of the location in the paper. The smaller the equilibrium coefficient is, the more reasonability the program is. The actual application shows that the location based on influence makes the location algorithm more reasonable and available.

本文针对基于R k NN（反向k最近邻）的空间定位影响评估和查询算法问题进行研究。一方面，一个对象可以对多个位置做出贡献。然而，对于用于评估空间位置的影响的现有措施，对象仅对一个位置做出贡献，并且其影响通常由该区域中空间对象的数量来衡量。在这种情况下，根据R k评估空间位置影响的新方法提出了NN。由于贡献的权重取决于对象与位置之间的距离，因此给出了影响权重的定义，这符合实际应用。另一方面，提出了一种基于空间测度的查询算法。首先，应用名为INCH（区间的凸包）的算法来获取所有对象都是候选对象的候选区域。然后，使用k NN和Range-k细化结果。然后，根据拟议的措施，R k中物体的权重计算NN结果，并累积位置的影响。实际数据的实验结果表明，优化算法在效率上优于基本算法。另外，为了在位置问题中提供最佳的客户服务并充分利用所有基础设施，提出了一种基于R k NN的带有查询的位置算法。在选址程序中计算每种设施的影响，并使用平衡系数评估论文中选址的合理性。平衡系数越小，程序的合理性就越高。实际应用表明，基于影响的定位使得定位算法更加合理和实用。