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In several applications, data objects move on pre-defined spatial networks such as road segments, railways, and invisible air routes. Many of these objects exhibit similarity with respect to their traversed paths, and therefore, two objects can be correlated based on their motion similarity. Useful information can be retrieved from these correlations and this knowledge can be used to define similarity classes. In this paper, the authors study similarity search for moving object trajectories in spatial networks. The problem poses some important challenges, since, it is quite different from the case where objects are allowed to move freely in any direction without motion restrictions.
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