Approximate aggregate nearest neighbor search on moving objects trajectories

作     者：Mohammad Reza Abbasifard Hassan Naderi Zohreh Fallahnejad Omid Isfahani Alamdari 

作者机构：MODB Lab. School of Computer Engineering Iran University of Science and Technology 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2015年第22卷第11期

页      面：4246-4253页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Approximate aggregate k nearest neighbor(AAk NN) s 

摘      要：Aggregate nearest neighbor(ANN) search retrieves for two spatial datasets T and Q, segment(s) of one or more trajectories from the set T having minimum aggregate distance to points in Q. When interacting with large amounts of trajectories, this process would be very time-consuming due to consecutive page loads. An approximate method for finding segments with minimum aggregate distance is proposed which can improve the response time. In order to index large volumes of trajectories, scalable and efficient trajectory index(SETI) structure is used. But some refinements are provided to temporal index of SETI to improve the performance of proposed method. The experiments were performed with different number of query points and percentages of dataset. It is shown that proposed method besides having an acceptable precision, can reduce the computation time significantly. It is also shown that the main fraction of search time among load time, ANN and computing convex and centroid, is related to ANN.