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.
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Wasinger, R. et al. (2013). Scrutable User Models and Personalised Item Recommendation in Mobile Lifestyle Applications. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38844-6_7
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DOI: https://doi.org/10.1007/978-3-642-38844-6_7
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