PTRAIL -- A python package for parallel trajectory data preprocessing
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Abstract (arXiv)
Trajectory data represent a trace of an object that changes its position in space over time. This kind of data is complex to handle and analyze, since it is generally produced in huge quantities, often prone to errors generated by the geolocation device, human mishandling, or area coverage limitation. Therefore, there is a need for software specifically tailored to preprocess trajectory data. In this work we propose PTRAIL, a python package offering several trajectory preprocessing steps, including filtering, feature extraction, and interpolation. PTRAIL uses parallel computation and vectorization, being suitable for large datasets and fast compared to other python libraries.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 0 of its 17 references that are in the map. First posted on arXiv 26 Aug 2021.
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Citing papers per year: 2023: 2; 2024: 0; 2025: 1; 2026: 1.
4 papers.
- 2023Survey of Federated Learning Models for Spatial-Temporal Mobility Applicationscited by 2
- 2023ANALYTiC: Understanding Decision Boundaries and Dimensionality Reduction in Machine Learningcited by 0
- 2025Towards Interpretable and Efficient Feature Selection in Trajectory Datasets: A Taxonomic Approachcited by 0
- 2026A Systematic Approach for Selecting Trajectories for Data Augmentationcited by 0
- 2026A Systematic Approach for Selecting Trajectories for Data Augmentation9 Jun 2026
- 2025Towards Interpretable and Efficient Feature Selection in Trajectory Datasets: A Taxonomic Approach25 Jun 2025
- 2023ANALYTiC: Understanding Decision Boundaries and Dimensionality Reduction in Machine Learning29 Dec 2023
- 2023Survey of Federated Learning Models for Spatial-Temporal Mobility Applications9 May 2023