/TrajLib

Trajectory Mining Library for Python

Primary LanguagePythonApache License 2.0Apache-2.0

Trajectory Mining Library for Python!

The aim of this library is to provide a simple python library for researchers who like to process trajectories. This library is in the early stage and we gradually add features to it.

example

animal dataset

take a look at TrajLib_Usage_Example.ipynb

geolife dataset

we create an example code "create_geolife_features.py" here that generates segment features and points features for Geolife dataset. This is not a full dataset and is filltered by one user. If you need to use the full geolife dataset, please run this code on the full dataset.

cite:

If you are using this library in your work, please cite to the following paper. This library is developed during the implementation of the paper.

link: https://link.springer.com/chapter/10.1007/978-3-319-89656-4_24

Etemad, M., Soares Júnior, A., & Matwin, S. (2018). Predicting Transportation Modes of GPS Trajectories using Feature Engineering and Noise Removal. In Advances in Artificial Intelligence: 31st Canadian Conference on Artificial Intelligence, Canadian AI 2018, Toronto, ON, Canada, May 8–11, 2018, Proceedings 31 (pp. 259-264). Springer International Publishing.

@inproceedings{etemad2018predicting,
  title={Predicting Transportation Modes of GPS Trajectories using Feature Engineering and Noise Removal},
  author={Etemad, Mohammad and Soares J{\'u}nior, Am{\'\i}lcar and Matwin, Stan},
  booktitle={Advances in Artificial Intelligence: 31st Canadian Conference on Artificial Intelligence, Canadian AI 2018, Toronto, ON, Canada, May 8--11, 2018, Proceedings 31},
  pages={259--264},
  year={2018},
  organization={Springer}
}