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SKOVAJSA, Š.
Original Title
Review of clustering methods used in data-driven housing market segmentation
English Title
Type
WoS Article
Original Abstract
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.
English abstract
Keywords
clustering algorithms; housing market analysis; housing market segmentation; data-driven segmentation
Key words in English
Authors
RIV year
2024
Released
08.09.2023
Publisher
Polish Real Estate Scientific Society
ISBN
1733-2478
Periodical
Real Estate Management and Valuation
Volume
31
Number
3
State
Republic of Poland
Pages from
66
Pages to
74
Pages count
8
URL
https://www.remv-journal.com/Review-of-clustering-methods-used-in-data-driven-housing-market-segmentation,162812,0,2.html
Full text in the Digital Library
http://hdl.handle.net/11012/214454
BibTex
@article{BUT184573, author="Štěpán {Skovajsa}", title="Review of clustering methods used in data-driven housing market segmentation", journal="Real Estate Management and Valuation", year="2023", volume="31", number="3", pages="66--74", doi="10.2478/remav-2023-0022 ", issn="1733-2478", url="https://www.remv-journal.com/Review-of-clustering-methods-used-in-data-driven-housing-market-segmentation,162812,0,2.html" }
Documents
10.2478_remav-2023-0022