Exploring Machine Learning's Application in Online Real Estate Marketplace
- DOI
- 10.2991/978-94-6463-102-9_144How to use a DOI?
- Keywords
- Machine-Learning-Driven Solution; Supervised Learning; Unsupervised Learning; Dimensionality Reduction; Real Estate Market
- Abstract
Due to the COVID-19 pandemic and the aggressive fiscal policy by the government, the US real estate market witnessed one of the biggest price jumps in history. A significant increase in both direct and indirect economic activities happened as a result. Our interest is to explore the opportunity of applying machine learning models in the real estate industry. Several data-driven products are available in the US market, such as the Zestimate feature on Zillow.com. However, the core algorithm of these products is largely unknown to the user, and more innovative use cases could be created. We want to demystify the mechanisms behind these products and develop a proof-of-concept of machine-learning-driven model application in this area.
In this paper, we leveraged a public dataset, which compiled listing records from Zillow.com, the largest online real estate listing platform. We explored supervised (implemented with XGBoost) and unsupervised machine learning (implemented with sklearn) methods and achieved promising results in both cases. We also proposed the design of potential commercial use cases and recommendations for improvements.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Zixuan Zhao PY - 2022 DA - 2022/12/29 TI - Exploring Machine Learning's Application in Online Real Estate Marketplace BT - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022) PB - Atlantis Press SP - 1383 EP - 1382 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-102-9_144 DO - 10.2991/978-94-6463-102-9_144 ID - Zhao2022 ER -