Towards a unified deep model for trajectory analysis.

SIGSPATIAL/GIS(2022)

Cited 0|Views27
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Abstract
Trajectory-based applications have acquired significant attention in several areas, including transportation (e.g., mapping and routing, traffic monitoring and forecasting), location-based service (e.g., recommendations), health (e.g., contact tracing), and urban planning. However, building such applications is still cumbersome due to the lack of unified frameworks to tackle the underlying trajectory problems, including trajectory similarity search, trajectory imputation, classification, prediction, and simplification. Despite the fact that all of these problems deal with the same trajectory data, each of the proposed solutions in the literature (e.g., see [7, 10] for surveys) is entirely designed to solve one problem of interest. This makes it hard to have a unified efficient and practical framework that is capable of supporting most (if not all) trajectory problems.
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Key words
unified deep model,trajectory
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