What recommender systems can learn from decision psychology about preference elicitation and behavioral change
ABSTRACT: Recommender systems typically use collaborative filtering: information from your preferences (i.e. your ratings) is combined with that of other users to predict what other items you might also like. Much of the research in the field has focused on building algorithms that provide the most accurate recommendations. However, these models make strong assumptions about how preferences come about, how stable they are, and how they can be measured. Having a background in decision psychology I have studied how the preference elicitation part of recommender systems (e.g., how the system learns your preference) can be better understood and improved based on psychological insights. I will discuss how our memory influences our ratings and why ratings (as an absolute measure of preference) have issues. I will also discuss recent work on other types of preference elicitation that use relative measures such as choice rather than rating.
Moreover, I will discuss new ideas on recommending for behavioral change: when people want to improve their behavior (become more sustainable, live a healthier life) we need different algorithms that do not predict what we choose or do now but what we should choose to improve on our behavior (Ekstrand and Willemsen, 2016). I will present work based on a Rasch scale as an example of such an alternative approach to recommendations. A Rasch scale orders behaviors in terms of their difficulty or costs and at the same time models a users’ ability to perform these behaviors. I will discuss a user study that implemented this Rasch scale to provide personalized suggestions in an energy-saving recommender system and another study that used the Rasch scale to model users’ ability towards lifestyle modifications to reduce hypertension.
BIO: Dr. Martijn Willemsen is an expert on human decision making in interactive systems. He works in the Human-Technology Interaction group of Eindhoven University of Technology (The Netherlands). His primary interests lie in the understanding of cognitive processes of decision making by means of process tracing and in the application of decision making theory in interactive systems such as recommender systems. He is also an expert on user-centric evaluation of adaptive systems.