Continuous K-Nearest Neighbor Queries for Uncertain Moving Objects
YU Yanwei1, QI Jianpeng1, SONG Peng1, ZHANG Yonggang2
1.School of Computer and Control Engineering, Yantai University, Yantai 264005 2.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012
Abstract:An urgent problem in location-based services is continuous K-nearest neighbor (KNN) queries for uncertain moving objects. An efficient algorithm for continuous K-nearest neighbor queries for uncertain moving objects is proposed. Firstly, two solutions, MaxMin and Rate, are proposed to predict the possible location range of the moving object in the time interval by utilizing the sampling points with velocities in the recent time window. A closed interval of minimum and maximum distances is employed to represent the distance between the query object and the moving object. Secondly, an optimized ranking method based on vague possibility decision is proposed to quickly find KNNs of the query object. Finally, experimental results on real and synthetic large-scale datasets demonstrate the effectiveness of the proposed algorithm.
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