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Evaluating Trajectory Queries over Imprecise Location Data

  • Xike Xie
  • Reynold Cheng
  • Man Lung Yiu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7338)

Abstract

Trajectory queries, which retrieve nearby objects for every point of a given route, can be used to identify alerts of potential threats along a vessel route, or monitor the adjacent rescuers to a travel path. However, the locations of these objects (e.g., threats, succours) may not be precisely obtained due to hardware limitations of measuring devices, as well as the constantly-changing nature of the external environment. Ignoring data uncertainty can render low query quality, and cause undesirable consequences such as missing alerts of threats and poor response time in rescue operations. Also, the query is quite time-consuming, since all the points on the trajectory are considered. In this paper, we study how to efficiently evaluate trajectory queries over imprecise location data, by proposing a new concept called the u-bisector. In general, the u-bisector is an extension of bisector to handle imprecise data. Based on the u-bisector, we design several novel filters to make our solution scalable to a long trajectory and a large database size. An extensive experimental study on real datasets suggests that our proposal produces better results than traditional solutions that do not consider data imprecision.

Keywords

Near Neighbor Query Point Error Score Neighbor Query Validity Interval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xike Xie
    • 1
  • Reynold Cheng
    • 2
  • Man Lung Yiu
    • 3
  1. 1.Aalborg UniversityDenmark
  2. 2.University of Hong KongHong Kong
  3. 3.Hong Kong Polytechnic UniversityHung HomHong Kong

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