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HELIOS Approach: Utilizing AI and LLM for Enhanced Homogeneity Identification in Real Estate Market Analysis

Authors :
Artur Janowski
Malgorzata Renigier-Bilozor
Source :
Applied Sciences, Vol 14, Iss 14, p 6135 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The concept of homogeneity in the real estate market is a well-known analysis aspect, yet it remains a significant challenge in practical implementation. This study aims to fill this research gap by introducing the HELIOS concept (Homogeneity Estate Linguistic Intelligence Omniscient Support), presenting a new approach to real estate market analyses. In a world increasingly mindful of environmental, social, and economic concerns, HELIOS is a novel concept grounded in linguistic intelligence and machine learning to reshape how we perceive and analyze real estate data. By exploring the synergies between human expertise and technological capabilities, HELIOS aims not only to enhance the efficiency of real estate analyses but also to contribute to the broader goal of sustainable and responsible data practices in the dynamic landscape of property markets. Additionally, the article formulates a set of assumptions and suggestions to improve the effectiveness and efficiency of homogeneity analysis in mass valuation, emphasizing the synergy between human knowledge and the potential of machine technology.

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
14
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.bc686c60f1fe487db587c8bb9e2edef2
Document Type :
article
Full Text :
https://doi.org/10.3390/app14146135