Machine learning (ML) and deep learning (DL) methods have recently become a hot topic in the real estate discipline. They have contributed to the advancement of various domains in real estate sector. This paper provides a critical review of recent trends in applying machine learning and deep learning (ML/DL) techniques in various domains of real estate and investigate their potential for the real estate sector. Recent advances in model development, testing and areas of application in real estate in the past 4 years (2017–2020) are presented. Findings reveal that 20 different ML and DL algorithms were utilized to examine various aspects of real estate development and valuation, and that the most commonly used algorithms are neural networks, regression models, random forest, booting, support vector machine and cubist/pruned model tree.
|Title of host publication||Artificial Intelligence Applications and Innovations - 18th IFIP WG 12.5 International Conference, AIAI 2022, Proceedings|
|Editors||Ilias Maglogiannis, Lazaros Iliadis, John Macintyre, Paulo Cortez|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||19|
|State||Published - 2022|
|Name||IFIP Advances in Information and Communication Technology|
Bibliographical noteFunding Information:
Acknowledgment. The author acknowledges the support of the King Fahd University of Petroleum and Minerals for the research project.
© 2022, IFIP International Federation for Information Processing.
- Deep learning
- Machine learning
- Real estate
ASJC Scopus subject areas
- Information Systems
- Computer Networks and Communications
- Information Systems and Management