Review of clustering methods used in data-driven housing market segmentation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26610%2F23%3APU148953" target="_blank" >RIV/00216305:26610/23:PU148953 - isvavai.cz</a>
Result on the web
<a href="https://www.remv-journal.com/Review-of-clustering-methods-used-in-data-driven-housing-market-segmentation,162812,0,2.html" target="_blank" >https://www.remv-journal.com/Review-of-clustering-methods-used-in-data-driven-housing-market-segmentation,162812,0,2.html</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.2478/remav-2023-0022" target="_blank" >10.2478/remav-2023-0022</a>

Result language
angličtina
Original language name
Review of clustering methods used in data-driven housing market segmentation
Original language description
There was already a huge effort spent to prove the existence of housing market segments, how to utilize them to improve valuation accuracy, and gain knowledge about the inner structure of the whole superior housing market. Accordingly, many different methods on the topic were explored, but there is still no universal framework known. The aim of this article is to review some previous studies on data-driven housing market segmentation methods with a focus on clustering methods and their ability to capture market segments with respect to the shape of clusters, fuzziness, and hierarchical structure.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
50202 - Applied Economics, Econometrics

Project
<a href="/en/project/EF19_073%2F0016948" target="_blank" >EF19_073/0016948: Quality internal grants at BUT</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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