In this repository we provide code of the paper:
PATE: Property, Amenities, Traffic and Emotions Coming Together for Real Estate Price Prediction
Yaping Zhao, Ramgopal Ravi, Shuhui Shi, Zhongrui Wang, Edmund Y. Lam, Jichang Zhao
arxiv link: https://arxiv.org/abs/2209.05471
The H4M Dataset is released at: https://indigopurple.github.io/H4M/index.html
- For pre-requisites, run:
conda env create -f environment.yml
conda activate pate
- To reproduce the results and figures in the paper, run:
python main.py
- For further research, visit the website of H4M Dataset.
Cite our paper if you find it interesting!
@misc{zhao2022pate,
title={PATE: Property, Amenities, Traffic and Emotions Coming Together for Real Estate Price Prediction},
author={Zhao, Yaping and Ravi, Ramgopal and Shi, Shuhui and Wang, Zhongrui and Lam, Edmund Y. and Zhao, Jichang},
journal={arXiv preprint arXiv:2209.05471},
year={2022}
}
@article{zhao2022h4m,
title={H4M: Heterogeneous, Multi-source, Multi-modal, Multi-view and Multi-distributional Dataset for Socioeconomic Analytics in the Case of Beijing},
author={Zhao, Yaping and Shi, Shuhui and Ravi, Ramgopal and Wang, Zhongrui and Lam, Edmund Y and Zhao, Jichang},
journal={arXiv preprint arXiv:2208.12542},
year={2022}
}