MediaFutures Seminar: Computing Biases in Recommender Systems with Marko Tkalčič, University of Primorska

Marko Tkalčič from the University of Primorska in Koper, Slovenia will give a seminar on April 14th.

TITLE: Computational Psychology in Recommender Systems

WHEN: 14 April, 13:30 – 14:1 

ABSTRACT:

Recommender systems are systems that help users in decision-making situations where there is an abundance of choices. We can find them in our everyday lives, for example in online shops. State-of-the-art research in recommender systems has shown the benefits of behavioural modeling. Behavioural modeling means that we use past ratings, purchases, clicks etc. to model the user preferences. However, behavioural modeling is not able to capture certain aspects of the user preferences. Behavioral modeling can amplify existing biases in datasets. In this talk I will show how the usage of complementary research in computational psychology, such as detection of personality and emotions, can help recommender systems to mitigate both data/algorithm biases and cognitive biases.

BIO:

Marko Tkalčič is associate professor at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) at the University of Primorska in Koper, Slovenia. He aims at improving personalized services (e.g. recommender systems) through the usage of psychological models in personalization algorithms. To achieve this, he uses diverse research methodologies, including data mining, machine learning, and user studies. He is editorial board member of the Springer UMUAI and Frontiers in Psychology journals and PC chair of the ACM UMAP 2021 conference.