Publication detail

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

SKOVAJSA, Š.

Original Title

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

Type

journal article in Web of Science

Language

English

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.

Keywords

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

Authors

SKOVAJSA, Š.

Released

8. 9. 2023

Publisher

Polish Real Estate Scientific Society

ISBN

1733-2478

Periodical

Real Estate Management and Valuation

Year of study

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"
}