  Trajectory classification tasks became more complex as large volumes of
mobility data are being generated every day and enriched with new sources of
information, such as social networks and IoT sensors. Fast classification
algorithms are essential for discovering knowledge in trajectory data for real
applications. In this work we propose a method for fast discovery of
subtrajectories with the reduction of the search space and the optimization of
the MASTERMovelets method, which has proven to be effective for discovering
interpretable patterns in classification problems.
