# Fast discovery of multidimensional subsequences for robust trajectory classification

arXiv: https://arxiv.org/abs/2102.04781 · HTML: https://mlsanity.com/paper/2102.04781/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 21 references that are in the map.
- First posted on arXiv 9 Feb 2021.

## Builds on (most cited first, 2 of 2)

- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [Inferring transportation modes from GPS trajectories using a convolutional neural network](https://mlsanity.com/paper/1804.02386/) (2018)

## Abstract (arXiv)

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.