A survey of trajectory distance measures and performance evaluation

The proliferation of trajectory data in various application domains has inspired tremendous research efforts to analyze large-scale trajectory data from a variety of aspects. A fundamental ingredient of these trajectory analysis tasks and applications is distance measures for effectively determining...

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Bibliographic Details
Published inThe VLDB journal Vol. 29; no. 1; pp. 3 - 32
Main Authors Su, Han, Liu, Shuncheng, Zheng, Bolong, Zhou, Xiaofang, Zheng, Kai
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2020
Springer Nature B.V
Subjects
Computer Science
Database Management
Distance measurement
Performance evaluation
Special Issue Paper
Trajectory analysis
Trajectory measurement
Trajectory transformation
Trajectory distance measure
Objective evaluation
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Summary:The proliferation of trajectory data in various application domains has inspired tremendous research efforts to analyze large-scale trajectory data from a variety of aspects. A fundamental ingredient of these trajectory analysis tasks and applications is distance measures for effectively determining how similar two trajectories are. We conduct a comprehensive survey of the trajectory distance measures. The trajectory distance measures are classified into four categories according to the trajectory data type and whether the temporal information is measured. In addition, the effectiveness and complexity of each distance measure are studied. The experimental study is also conducted on their effectiveness in the six different trajectory transformations.
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ISSN:1066-8888
0949-877X
DOI:10.1007/s00778-019-00574-9