Research On K-nearest Neighbor And Reverse-k-nearest Neighbor Query Based On Comprehensive Evaluation In Obstacle Space

In real life,many problems are composed of multiple factors that conflict and affect each other.People often encounter situations where multiple factors need to be considered to make the final decision.The spatial query method within the existing obstacle distance can not solve this kind of problem well.Aiming at this problem,we propose a comprehensive evaluation k-nearest neighbor query algorithm and a comprehensive evaluation reverse k-nearest neighbor query algorithm in the obstacle space.The main contents are as follows:Firstly,considering the multiple factors,comprehensive evaluation is made,and the comprehensive evaluation result algorithm is given and the influence of the evaluation index on the evaluation result is analyzed,the hotel selection example considering multiple factors is used to illustrate that idea.The comprehensive evaluation thought is applied to the k-nearest neighbor query,and the k-nearest neighbor query algorithm based on comprehensive evaluation in the obstacle space is proposed,and a total of k query results based on the comprehensive weight index are obtained.The algorithm is introduced in detail,and the specific execution steps and algorithm analysis are given.Secondly,the comprehensive evaluation thought is applied to the reverse k-nearest neighbor query,and the reverse k-nearest neighbor query algorithm based on comprehensive evaluation in the obstacle space is proposed.A total of k query results based on the comprehensive weight index are obtained,the algorithm is introduced in detail,and the specific execution steps and algorithm analysis of the algorithm are given.Finally,by constructing the experimental systems of the k-nearest neighbor query algorithm based on comprehensive evaluation in the obstacle space and the reverse k-nearest neighbor query algorithm,the k-nearest neighbor and reverse k-neighbor query operations based on comprehensive evaluation are performed.With the support of the experimental system,the traditional method is compared with the k-nearest neighbor and reverse k-neighbor query algorithm based on comprehensive evaluation in the same experimental environment by transforming the attribute dataset and experimentalparameters.The experimental results show that the proposed algorithm has better performance in spatial query.