Journal of Central South University

, Volume 22, Issue 11, pp 4246–4253

Approximate aggregate nearest neighbor search on moving objects trajectories

  • Mohammad Reza Abbasifard
  • Hassan Naderi
  • Zohreh Fallahnejad
  • Omid Isfahani Alamdari
Article
  • 56 Downloads

Abstract

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.

Key words

Approximate aggregate k nearest neighbor (AAkNN) scalable and efficient trajectory index (SETI) trajectory indexing moving objects query processing 

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Copyright information

© Central South University Press and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Mohammad Reza Abbasifard
    • 1
  • Hassan Naderi
    • 1
  • Zohreh Fallahnejad
    • 1
  • Omid Isfahani Alamdari
    • 1
  1. 1.MODB Lab., School of Computer EngineeringIran University of Science and TechnologyTehranIran

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