Principles for creating an intelligent expert system for real estate investment analysis based on machine learning and GIS

GIS Technologies for Decision-Making and Management

Authors

First and Last Name	Academic degree	E-mail	Affiliation
Оlena Pomortseva	Ph.D.	elenapomor7 [at] gmail.com	V.N. Karazin Kharkiv National University Kharkiv , Ukraine
Sergiy Kobzan	Ph.D.	s.kobzan [at] gmail.com	O.M. Beketov National University of Urban Economy Kharkiv , Ukraine
Volodymyr Pankiv	No	peacekeaper7 [at] gmail.com	V.N. Karazin Kharkiv National University Kharkiv, Ukraine
Danylo Kin	Ph.D.	kondanil24 [at] gmail.com	Kyiv National University of Construction and Architecture Kyiv , Ukraine

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 18.08.2025 - 21:14

Abstract

The purpose of this article is to explore how geospatial artificial intelligence can support decision-making in the real estate market. Today, real estate stakeholders need to work with large and constantly updated datasets. These datasets often have a spatial dimension that must be considered when identifying patterns and building forecasts. To address this need, the authors propose the use of geographic information systems in combination with geospatial artificial intelligence tools. The problem discussed in the article is approached through the development of a model that integrates artificial intelligence with geographic information systems technologies. By applying machine learning algorithms, it becomes possible to analyze large volumes of diverse data and discover hidden trends and relationships. The results of this study may be useful for a wide range of real estate professionals – including agents, appraisers, investors, and other stakeholders. The article demonstrates the potential of combining GIS and AI – an approach that is particularly relevant not only today, but also in the context of rebuilding and developing the real estate sector in the post-war period.

Keywords

Geoinformation system; Database; Dataset; Artificial intelligence; Real estate; Expert system; real estate market

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