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.

翻译：本文提出ST-RAP——一种新型的房地产评估时空框架。该框架采用分层架构，结合异构图神经网络，同步捕获时间动态与空间关联。基于大规模房地产数据集的全面实验表明，ST-RAP在性能上超越既有方法，验证了时空维度整合对房地产评估的显著优势。相关代码与数据集已开源至https://github.com/dojeon-ai/STRAP。