KG for socioeconomic indicator prediction

This is the codebase for "Hierarchical Knowledge Graph Learning Enabled Socioeconomic Indicator Prediction in Location-Based Social Network"(WWW'23).
NYC dataset is included.

Installation

Environment

• Tested OS: Linux
• Python >= 3.8
• PyTorch == 1.9.0
• torch_geometric == 1.7.2

Dependencies

1. Install PyTorch 1.9.0 with the correct CUDA version.
2. Use the pip install -r requirements.txt command to install all of the Python modules and packages used in this project.

Usage

Please first download "mob-adj.npy" from here and put it into "./data/data_ny/" folder.

Train:

bash run.sh

Evaluate:

python evaluate.py

Reference

If you found this library useful in your research, please consider citing:

@inproceedings{zhou2023hierarchical,
  title={Hierarchical knowledge graph learning enabled socioeconomic indicator prediction in location-based social network},
  author={Zhou, Zhilun and Liu, Yu and Ding, Jingtao and Jin, Depeng and Li, Yong},
  booktitle={Proceedings of the ACM Web Conference 2023},
  pages={122--132},
  year={2023}
}