IDEAS home Printed from https://ideas.repec.org/a/taf/tbitxx/v38y2019i9p950-958.html
   My bibliography  Save this article

Applying big data and stream processing to the real estate domain

Author

Listed:
  • Herminio García-González
  • Daniel Fernández-Álvarez
  • José Emilio Labra-Gayo
  • Patricia Ordóñez de Pablos

Abstract

In this paper, we propose an architecture that combines Big Data and Stream Processing which can be applied to the Real Estate Domain. Our approach consists of a specialisation of Lambda architecture and it is inspired by some aspects of Kappa architecture. As a proof of this solution, we show a prototype developed following it and a comparison of the three architecture quality models. Finally, we highlight the differences between the proposed architecture and similar ones and draw some future lines following the present approach.

Suggested Citation

  • Herminio García-González & Daniel Fernández-Álvarez & José Emilio Labra-Gayo & Patricia Ordóñez de Pablos, 2019. "Applying big data and stream processing to the real estate domain," Behaviour and Information Technology, Taylor & Francis Journals, vol. 38(9), pages 950-958, September.
  • Handle: RePEc:taf:tbitxx:v:38:y:2019:i:9:p:950-958
    DOI: 10.1080/0144929X.2019.1620858
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0144929X.2019.1620858
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0144929X.2019.1620858?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tbitxx:v:38:y:2019:i:9:p:950-958. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tbit .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.