Research On Nearest Neighbor Query Method Of Mixed Complex Data In Spatial Database

In recent years,with the development of Internet technology and global positioning technology,nearest neighbor query is widely used in location information retrieval and it is also important in fields of image retrieval,pattern recognition and machine learning.The existing query methods are mainly reflected in the neighbor query of points and points,the neighbor query of points and line segments,line segments and line segments,but cannot directly solve the neighbor query problem of complex data with mixed points and line segments.In order to make up for the deficiencies of existing methods,nearest neighbor query method for mixing complex data of points and line segments is proposed in this paper.In order to solve the nearest neighbor query problem of mixed data in Euclidean space,whether the query object is a query point or a query line segment is judged.The data is firstly pruned by the Voronoi diagram to reduce the number of data objects,two data set reduction algorithms of NN?FILTER(Point P,Line L)and LNN?FILTER(Point P,Line L)are given.Then the distance between the point and the line segment is calculated according to the coordinate method and the vector algorithm,and then by judging the positional relationship between the line segment and the line segment,the distance between the line segment and the line segment is calculated by calculating the distance between the point and the line segment.A short distance is determined among the two shortest distances,so that the nearest one can be accurately found.Two data set refinement algorithms of QMDNN?REFINE algorithm and LMDNN?REFINE algorithm are given.Theoretical and experimental studies show that the proposed algorithm can effectively deal with the nearest neighbor problem of mixed complex data.The nearest neighbor query problem in the road network environment is further studied.Firstly,the data set is pre-processed,and an Array(q,P,L)algorithm is proposed,so that the intersection of the line segment and the road network and the data line segment form a mapping,and the data point and the H value of the cell where it is formed are also mapped.Then the QHR-tree index and the shortest path theorem are used to reduce the mixed data set of points and line segments to obtain the NMNN?FILTER(q)algorithm.Then the points in the filtered set are trimed.The shortest distance from the query points to the points in the candidate set is calculated.Compared to the shortest distances,the NMNN?Search(q)algorithm is obtained and the nearest neighbor query result is obtained accurately.This method solves the problem of mixed data nearest neighbor in the road network environment.