Detail publikace

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

SKOVAJSA, Š.

Originální název

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

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

clustering algorithms; housing market analysis; housing market segmentation; data-driven segmentation

Autoři

SKOVAJSA, Š.

Vydáno

8. 9. 2023

Nakladatel

Polish Real Estate Scientific Society

ISSN

1733-2478

Periodikum

Real Estate Management and Valuation

Ročník

31

Číslo

3

Stát

Polská republika

Strany od

66

Strany do

74

Strany počet

8

URL

https://www.remv-journal.com/Review-of-clustering-methods-used-in-data-driven-housing-market-segmentation,162812,0,2.html

Plný text v Digitální knihovně

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"
}