Scrutable User Models and Personalised Item Recommendation in Mobile Lifestyle Applications

  • Rainer Wasinger
  • James Wallbank
  • Luiz Pizzato
  • Judy Kay
  • Bob Kummerfeld
  • Matthias Böhmer
  • Antonio Krüger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7899)

Abstract

This paper presents our work on supporting scrutable user models for use in mobile applications that provide personalised item recommendations. In particular, we describe a mobile lifestyle application in the fine-dining domain, designed to recommend meals at a particular restaurant based on a person’s user model. The contributions of this work are three-fold. First is the mobile application and its personalisation engine for item recommendation using a content and critique-based hybrid recommender. Second, we illustrate the control and scrutability that a user has in configuring their user model and browsing a content list. Thirdly, this is validated in a user experiment that illustrates how new digital features may revolutionise the way that paper-based systems (like restaurant menus) currently work. Although this work is based on restaurant menu recommendations, its approach to scrutability and mobile client-side personalisation carry across to a broad class of commercial applications.

Keywords

Mobile personalisation user modelling scrutability recommender technology 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rainer Wasinger
    • 1
  • James Wallbank
    • 1
  • Luiz Pizzato
    • 1
  • Judy Kay
    • 1
  • Bob Kummerfeld
    • 1
  • Matthias Böhmer
    • 2
  • Antonio Krüger
    • 2
  1. 1.School of Information TechnologiesThe University of SydneyAustralia
  2. 2.DFKI GmbHSaarbrückenGermany

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