An evaluation and query algorithm for the influence of spatial location based on R k NN
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An evaluation and query algorithm for the influence of spatial location based on RkNN Jingke XU 3
1,2,3
, Yidan ZHAO2, Ge YU1
1 School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China 2 School of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction, Shenyang 110168, China
c Higher Education Press 2020
Abstract 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.
in many database applications and widely applied to the buildings planning and layout [1]. The existing method for evaluating the influence of a given spatial location s is to calculate the sum of spatial objects affected by s. It can be determined whether a spatial object o is affected by the Voronoi diagram [2] or RNN query [3]. Calculate the distance between o and s, if the distance is the smallest of all distances, then s affects o; otherwise, s cannot affect o. It can be seen from the Fig. 1, select one or more of the appropriate locations from many candidate locations (P1 , P2 , P3 , and P4 ) to build infrastructure such as post office or shopping center, the criterion of choice is which locat
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