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Human-Machine Synergy in Real Estate Similarity Concept

Author

Listed:
  • Renigier-Biłozor Małgorzata

    (Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Michała Oczapowskiego 2, 10-719 Olsztyn, Poland)

  • Janowski Artur

    (Institute of Geodesy and Construction, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, ul. Michała Oczapowskiego 2, 10-719 Olsztyn, Poland)

Abstract

The issue of similarity in the real estate market is a widely recognized aspect of analysis, yet it remains underexplored in scientific research. This study aims to address this gap by introducing the concept of a Property Cognitive Information System (PCIS), which offers an innovative approach to analyzing similarity in the real estate market. The PCIS introduces non-classical and alternative solutions, departing from the conventional data analysis practices commonly employed in the real estate market. Moreover, the study delves into the integration of artificial intelligence (AI) in the PCIS. The paper highlights the value added by the PCIS, specifically discussing the validity of using automatic ML-based solutions to objectify the results of synergistic data processing in the real estate market. Furthermore, the article establishes a set of essential assumptions and recommendations that contribute to a well-defined and interpretable notion of similarity in the context of human-machine analyses. By exploring the intricacies of similarity in the real estate market through the innovative PCIS and AI-based solutions, this research seeks to broaden the understanding and applicability of data analysis techniques in this domain.

Suggested Citation

  • Renigier-Biłozor Małgorzata & Janowski Artur, 2024. "Human-Machine Synergy in Real Estate Similarity Concept," Real Estate Management and Valuation, Sciendo, vol. 32(2), pages 13-30.
    • Handle: RePEc:vrs:remava:v:32:y:2024:i:2:p:13-30:n:1002
    DOI: 10.2478/remav-2024-0010
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    References listed on IDEAS

    as
    1. Eli Beracha & M. Babajide Wintoki, 2013. "Forecasting Residential Real Estate Price Changes from Online Search Activity," Journal of Real Estate Research, American Real Estate Society, vol. 35(3), pages 283-312.
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    3. Andrey D. Pavlov, 2000. "Space-Varying Regression Coefficients: A Semi-parametric Approach Applied to Real Estate Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 28(2), pages 249-283.
    4. Anna C. Belkina & Christopher O. Ciccolella & Rina Anno & Richard Halpert & Josef Spidlen & Jennifer E. Snyder-Cappione, 2019. "Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
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    Keywords

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    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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