Going Beyond Popularity and Positivity Bias: Correcting Multifactorial Bias in Recommender Systems - M1.7

Explore a conference talk that delves into advanced techniques for addressing multifactorial bias in recommender systems. Learn how researchers are moving beyond traditional approaches to popularity and positivity bias correction. Discover the innovative methods proposed by Jin Huang, Harrie Oosterhuis, Masoud Mansoury, Herke van Hoof, and Maarten de Rijke to enhance fairness in recommendation algorithms. Gain insights into the latest developments in the field of recommender systems and their implications for creating more equitable and balanced recommendations across various domains.