Real Estate Appraisal

Real estate appraisal aims to accurately estimate property values, a crucial task with implications for finance and urban planning. Current research focuses on improving appraisal accuracy and efficiency through advanced machine learning models, incorporating diverse data sources like Points of Interest (POIs), spatial relationships (e.g., using graph neural networks and areal embeddings), and temporal dynamics. These advancements leverage techniques such as self-supervised learning, particularly for data-scarce regions, and aim to reduce reliance on subjective expert judgment, ultimately leading to more robust and reliable property valuations.