Elisabeth Lex, Markus Schedl,
"Psychology-informed Recommender Systems: A Human-centric Perspective on Recommender Systems"
: Proceedings of the 7th ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2022), 3-2022
Original Titel:
Psychology-informed Recommender Systems: A Human-centric Perspective on Recommender Systems
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the 7th ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2022)
Original Kurzfassung:
Personalized recommender systems are essential tools to facilitate human decision making. Many contemporary recommender systems use advanced machine learning techniques to model
and predict user preferences from behavioral data. While such systems can provide helpful recommendations, their algorithms? design does not incorporate the underlying psychological mechanisms that shape user preferences and behavior.
In this tutorial, we will guide the attendees through the state-of-the-art in psychology-informed recommender systems, i.e., recommender systems that consider extrinsic and intrinsic human factors. We show how such systems
can improve the recommendation process in a user-centric fashion.