IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v09y2010i05ns0219622010004019.html
   My bibliography  Save this article

Exploiting Image Content In Location-Based Shopping Recommender Systems For Mobile Users

Author

Listed:
  • O. O. OLUGBARA

    (Department of Information Technology, Durban University of Technology, Durban 4001, South Africa)

  • S. O. OJO

    (Faculty of Information and Communication Technology, Tshwane University of Technology, Pretoria 0001, South Africa)

  • M. I. MPHAHLELE

    (Department of Computer Networks, Tshwane University of Technology, Pretoria 0001, South Africa)

Abstract

This paper demonstrates how image content can be used to realize a location-based shopping recommender system for intuitively supporting mobile users in decision making. Generic Fourier Descriptors (GFD) image content of an item was extracted to exploit knowledge contained in item and user profile databases for learning to rank recommendations. Analytic Hierarchy Process (AHP) was used to automatically select a query item from a user profile. Single Criterion Decision Ranking (SCDR) and Multiple-Criteria Decision-Ranking (MCDR) techniques were compared to study the effect of multidimensional ratings of items on recommendations effectiveness. The SCDR and MCDR techniques are, respectively, based on Image Content Similarity Score (ICSS) and Relative Ratio (RR) aggregating function. Experimental results of a real user study showed that an MCDR system increases user satisfaction and improves recommendations effectiveness better than an SCDR system.

Suggested Citation

  • O. O. Olugbara & S. O. Ojo & M. I. Mphahlele, 2010. "Exploiting Image Content In Location-Based Shopping Recommender Systems For Mobile Users," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 9(05), pages 759-778.
  • Handle: RePEc:wsi:ijitdm:v:09:y:2010:i:05:n:s0219622010004019
    DOI: 10.1142/S0219622010004019
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622010004019
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219622010004019?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.

    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:wsi:ijitdm:v:09:y:2010:i:05:n:s0219622010004019. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    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.