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

arXiv: https://arxiv.org/abs/2308.10609 · HTML: https://mlsanity.com/paper/2308.10609/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 37 references that are in the map.
- First posted on arXiv 21 Aug 2023.

## Builds on (most cited first, 16 of 16)

- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [Graph Attention Networks](https://mlsanity.com/paper/1710.10903/) (2017)
- [Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling](https://mlsanity.com/paper/1412.3555/) (2014)
- [Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting](https://mlsanity.com/paper/2012.07436/) (2020)
- [Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting](https://mlsanity.com/paper/2106.13008/) (2021)
- [Are Transformers Effective for Time Series Forecasting?](https://mlsanity.com/paper/2205.13504/) (2022)
- [Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting](https://mlsanity.com/paper/1907.00235/) (2019)
- [Transformers in Time Series: A Survey](https://mlsanity.com/paper/2202.07125/) (2022)
- [Spatial-Temporal Transformer Networks for Traffic Flow Forecasting](https://mlsanity.com/paper/2001.02908/) (2020)
- [Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting--Full Version](https://mlsanity.com/paper/2204.13767/) (2022)
- [MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal](https://mlsanity.com/paper/2107.05180/) (2021)
- [Take a Look Around: Using Street View and Satellite Images to Estimate House Prices](https://mlsanity.com/paper/1807.07155/) (2018)
- [Vision-based Real Estate Price Estimation](https://mlsanity.com/paper/1707.05489/) (2017)
- [A Contextual Master-Slave Framework on Urban Region Graph for Urban Village Detection](https://mlsanity.com/paper/2211.14633/) (2022)
- [DraftRec: Personalized Draft Recommendation for Winning in Multi-Player Online Battle Arena Games](https://mlsanity.com/paper/2204.12750/) (2022)
- [Look Around! A Neighbor Relation Graph Learning Framework for Real Estate Appraisal](https://mlsanity.com/paper/2212.12190/) (2022)

## Built on by (most cited first, 5 of 5)

- [On the Performance of LLMs for Real Estate Appraisal](https://mlsanity.com/paper/2506.11812/) (2025)
- [Improving Real Estate Appraisal with POI Integration and Areal Embedding](https://mlsanity.com/paper/2311.11812/) (2023)
- [Multimodal Machine Learning for Real Estate Appraisal: A Comprehensive Survey](https://mlsanity.com/paper/2503.22119/) (2025)
- [ARED: Argentina Real Estate Dataset](https://mlsanity.com/paper/2403.00273/) (2024)
- [Meta-Transfer Learning Powered Temporal Graph Networks for Cross-City Real Estate Appraisal](https://mlsanity.com/paper/2410.08947/) (2024)

## Abstract (arXiv)

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.