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Data Mines in Real Estate Web Pages: Investigation of Changes in the Czech Real Estate Market Based on Elasticity and on Modified Price Volume Indicator

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F21%3A39918512" target="_blank" >RIV/00216275:25530/21:39918512 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-030-87869-6_15" target="_blank" >http://dx.doi.org/10.1007/978-3-030-87869-6_15</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-87869-6_15" target="_blank" >10.1007/978-3-030-87869-6_15</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Data Mines in Real Estate Web Pages: Investigation of Changes in the Czech Real Estate Market Based on Elasticity and on Modified Price Volume Indicator

  • Original language description

    A vast number of advertisements on the websites of real estate companies form deep unexplored data mines. Real estate data can be obtained daily by parsing such websites automatically. Specifically, data on the area of apartments and its price are commonly available. Thus, the real estate market could be inspected in each municipality of the Czech Republic. We have developed our own software tool for obtaining this data; it collected data during the period between June 2019 and March 2021. In addition to the price, we also monitored the number of advertisements in each municipality daily. The aim of this study is to propose a methodology for comparing the development of the real estate market in different districts. The comparison of regions is based on cluster analysis. In our study, each region was represented by 29 monthly averages of the number of advertisements and 29 monthly averages of average apartment prices per 1 m(2). However, we performed clustering on derived variables: the monthly value of elasticity and a modified price-volume indicator. The obtained clusters are graphically represented. In addition, the structure of market changes over time is economically interpreted.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    16TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS (SOCO 2021)

  • ISBN

    978-3-030-87869-6

  • ISSN

    2194-5357

  • e-ISSN

    2194-5365

  • Number of pages

    10

  • Pages from-to

    155-164

  • Publisher name

    SPRINGER INTERNATIONAL PUBLISHING AG

  • Place of publication

    CHAM

  • Event location

    Bilbao

  • Event date

    Sep 22, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000719656700015