Abstract
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.
| Original language | English |
|---|---|
| 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 |
| Pages | 231-249 |
| Number of pages | 19 |
| ISBN (Print) | 9783031083365 |
| DOIs | |
| State | Published - 2022 |
Publication series
| Name | IFIP Advances in Information and Communication Technology |
|---|---|
| Volume | 647 IFIP |
| ISSN (Print) | 1868-4238 |
| ISSN (Electronic) | 1868-422X |
Bibliographical note
Publisher Copyright:© 2022, IFIP International Federation for Information Processing.
Keywords
- Deep learning
- Machine learning
- Properties
- Real estate
ASJC Scopus subject areas
- Information Systems
- Computer Networks and Communications
- Information Systems and Management