ST-RAP: A Spatio-Temporal Framework for Real Estate Appraisal

Hojoon Lee, Hawon Jeong, Byungkun Lee, Kyungyup Lee, Jaegul Choo
8/21/2023
cs.LG

Official code: dojeon-ai/STRAP (15 stars, last commit 2023-08-22).

Abstract

In this paper, we introduce ST-RAP, a novel Spatio-Temporal framework for Real estate APpraisal. ST-RAP employs a hierarchical architecture with a heterogeneous graph neural network to encapsulate temporal dynamics and spatial relationships simultaneously. Through comprehensive experiments on a large-scale real estate dataset, ST-RAP outperforms previous methods, demonstrating the significant benefits of integrating spatial and temporal aspects in real estate appraisal. Our code and dataset are available at https://github.com/dojeon-ai/STRAP.

View on arXivView PDF

Code Implementations(1)

dojeon-ai/STRAPOfficial100%

Code for the paper "STRAP: A Spatio-Temporal Framework for Real Estate Apprisal" (CIKM 2023)

151Python, Jupyter NotebookAug 11, 20233 years ago

Cite this paper

@article{lee2023strap,
  title  = {ST-RAP: A Spatio-Temporal Framework for Real Estate Appraisal},
  author = {Hojoon Lee and Hawon Jeong and Byungkun Lee and Kyungyup Lee and Jaegul Choo},
  year   = {2023},
  eprint = {2308.10609},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.10609v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2308.10609.svg)](https://codeofpaper.com/paper/2308.10609)

Discussion