daima2017 / TKBC

An Interpretable Multi-hop Reasoning (IMR) model for temporal KG forecasting.

TKBC-IMR

An Interpretable Multi-hop Reasoning (IMR) model for temporal KG forecasting.

This is the code of paper Interpretable Multi-hop Reasoning for Forecasting Future Links on Temporal Knowledge Graphs. Zongwei Liang, Junan Yang, Keju Huang, Hui Liu.

Dependencies

    pip install -r requirements.txt

Results

• Dataset in TITer

• The result

Reproduce the Results

    bash ./run_ICEW18.sh
    bash ./run_ICEWS14.sh
    bash ./run_WIKI.sh
    bash ./run_YAGO.sh

Citation

If you find this code useful, please consider citing the following paper.

@inproceedings{
anonymous2022interpretable,
title={Interpretable Multi-hop Reasoning for Forecasting Future Links on Temporal Knowledge Graphs},
author={Anonymous},
booktitle={Submitted to The Tenth International Conference on Learning Representations },
year={2022},
url={https://openreview.net/forum?id=OQo6Tuyo0ih},
note={under review}
}

If you have any questions, please email me.

Acknowledgement

We refer to the code of xERTE. Thanks for their contributions.