Machine Learning Applications in Real Estate: Critical Review of Recent Development

Jamal Al-Qawasmi

doi:10.1007/978-3-031-08337-2_20

Machine Learning Applications in Real Estate: Critical Review of Recent Development

Jamal Al-Qawasmi^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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	https://doi.org/10.1007/978-3-031-08337-2_20
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

Funding Information:
Acknowledgment. The author acknowledges the support of the King Fahd University of Petroleum and Minerals for the research project.

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

Access to Document

10.1007/978-3-031-08337-2_20

Cite this

Al-Qawasmi, J. (2022). Machine Learning Applications in Real Estate: Critical Review of Recent Development. In I. Maglogiannis, L. Iliadis, J. Macintyre, & P. Cortez (Eds.), Artificial Intelligence Applications and Innovations - 18th IFIP WG 12.5 International Conference, AIAI 2022, Proceedings (pp. 231-249). (IFIP Advances in Information and Communication Technology; Vol. 647 IFIP). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-08337-2_20

Al-Qawasmi, Jamal. / Machine Learning Applications in Real Estate : Critical Review of Recent Development. Artificial Intelligence Applications and Innovations - 18th IFIP WG 12.5 International Conference, AIAI 2022, Proceedings. editor / Ilias Maglogiannis ; Lazaros Iliadis ; John Macintyre ; Paulo Cortez. Springer Science and Business Media Deutschland GmbH, 2022. pp. 231-249 (IFIP Advances in Information and Communication Technology).

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title = "Machine Learning Applications in Real Estate: Critical Review of Recent Development",

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.",

keywords = "Deep learning, Machine learning, Properties, Real estate",

author = "Jamal Al-Qawasmi",

note = "Funding Information: Acknowledgment. The author acknowledges the support of the King Fahd University of Petroleum and Minerals for the research project. Publisher Copyright: {\textcopyright} 2022, IFIP International Federation for Information Processing.",

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doi = "10.1007/978-3-031-08337-2_20",

language = "English",

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series = "IFIP Advances in Information and Communication Technology",

publisher = "Springer Science and Business Media Deutschland GmbH",

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editor = "Ilias Maglogiannis and Lazaros Iliadis and John Macintyre and Paulo Cortez",

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Al-Qawasmi, J 2022, Machine Learning Applications in Real Estate: Critical Review of Recent Development. in I Maglogiannis, L Iliadis, J Macintyre & P Cortez (eds), Artificial Intelligence Applications and Innovations - 18th IFIP WG 12.5 International Conference, AIAI 2022, Proceedings. IFIP Advances in Information and Communication Technology, vol. 647 IFIP, Springer Science and Business Media Deutschland GmbH, pp. 231-249. https://doi.org/10.1007/978-3-031-08337-2_20

Machine Learning Applications in Real Estate: Critical Review of Recent Development. / Al-Qawasmi, Jamal.
Artificial Intelligence Applications and Innovations - 18th IFIP WG 12.5 International Conference, AIAI 2022, Proceedings. ed. / Ilias Maglogiannis; Lazaros Iliadis; John Macintyre; Paulo Cortez. Springer Science and Business Media Deutschland GmbH, 2022. p. 231-249 (IFIP Advances in Information and Communication Technology; Vol. 647 IFIP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Machine Learning Applications in Real Estate

T2 - Critical Review of Recent Development

AU - Al-Qawasmi, Jamal

N1 - Funding Information: Acknowledgment. The author acknowledges the support of the King Fahd University of Petroleum and Minerals for the research project. Publisher Copyright: © 2022, IFIP International Federation for Information Processing.

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Deep learning

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Al-Qawasmi J. Machine Learning Applications in Real Estate: Critical Review of Recent Development. In Maglogiannis I, Iliadis L, Macintyre J, Cortez P, editors, Artificial Intelligence Applications and Innovations - 18th IFIP WG 12.5 International Conference, AIAI 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 231-249. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-031-08337-2_20

Machine Learning Applications in Real Estate: Critical Review of Recent Development

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this