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

In: Sandra Carberry , Stephan Weibelzahl , Alessandro Micarelli , Giovanni Semeraro (Hrsg.). User Modeling, Adaptation, and Personalization. Seiten 77-88 Lecture Notes in Computer Science (LNCS) 7899 ISBN 978-3-642-38843-9 Springer Berlin - Heidelberg 2013.


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.

Weitere Links

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence