Next location prediction

Install

Install the package in edit mode using:

pip install -e .

Neural network implementation

mobpredict/networks/ contains network implementation for multi-head self-attentional (MHSA) model and LSTM models.

Training

Run

python example/run.py

with training: True in example/config/config.yml file. The code will train a neural network for next location prediction with a dataset generated from mobility-simulation. The train_dataset shall be avilable as a .csv file stored in data_save_root. The other hyper parameters are defined in the config yml file. A folder with specified folder name (run_name) containing the trained nn parameters will be created in run_save_root.

Inference

Run

python example/run.py

with training: False in example/config/config.yml file. The code will take an already trained neural network for next location prediction, stored in run_save_root with dir name pretrain_dir, for inference for all datasets stored in data_save_root under the dir inference_data_dir. The datasets shall be in the format generated with mobility-simulation. A folder containing the evaluation results will be created in run_save_root.

We provide an already trained model with the default config parameters on the provided dtepr dataset.

Known issues:

None

TODO:

None

Citation

If you find this code useful for your work or use it in your project, please consider citing:

@misc{hong_revealing_2023,
    title={Revealing behavioral impact on mobility prediction networks through causal interventions},
    author={Hong, Ye and Xin, Yanan and Dirmeier, Simon and Perez-Cruz, Fernando and Raubal, Martin},
    publisher={arXiv},
    year={2023},
    url = {https://arxiv.org/abs/2311.11749},
    doi = {10.48550/arXiv.2311.11749},
}

Contact

If you have any questions, open an issue or let me know:

• Ye Hong {[email protected]}