ST-RAP: A Spatio-Temporal Framework for Real Estate Appraisal
It addresses real estate appraisal for property valuation, with incremental improvements in modeling spatio-temporal aspects.
The paper tackles real estate appraisal by developing ST-RAP, a spatio-temporal framework that integrates temporal dynamics and spatial relationships, and it outperforms previous methods on a large-scale dataset.
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.