Axia Valuers

An artificial intelligence algorithm analyzing 30 years of research in mass appraisals

Keywords: Multidimensional Scaling; Bibliometric Mapping; Knowledge Management; Mass Appraisal; Property
Valuation; Geographically Weighted Regression; Multiple Regression Analysis (MRA); Artificial Neural Networks;

Abstract: The research papers issued in scientific journals, for a variety of thematic areas, are not only increasing, nonetheless
exhibit an exponential growth over the last years. Accordingly, the researchers, struggle to retrieve information
apropos of novel knowledge and get informed in their field, while the rigor and at the same time, the extensive
composition of surveys, reviews, and overviews of research works, has become difficult or even impossible, as the
number of the available research studies is enormous. However, such reviews, contain vital information regarding
the evolution of a scientific subject, the trends of the literature, the most significant concepts, and the concealed
associations among research papers, their references, as well as authors’ clusters. In this work, a scientometric study
of the relevant to Mass Appraisals literature is for a first time accomplished, regarding the numerical models,
computational procedures, and automated methods, utilized in the Mass Appraisals and Property Valuations
literature. The study is based on an adequate pool of papers, constituted in Scopus database, utilizing a machine
learning algorithm developed from one of the authors, for multidimensional scaling and clustering of the keywords
found in the papers’ database, the authors and their cooperation and the co-occurrences of the references in the
papers studied. The time-series of the most frequent keywords are also computed, demonstrating the evolution of
the mass appraisals research and identifying future trends.

Download the full article here