A Lightweight Method for Modeling Confidence in Recommendations with Learned Beta Distributions
Norman Knyazev, Harrie Oosterhuis · 2023
Most recommender systems (RecSys) do not provide an indication of confidence in their decisions. Therefore, they do not distinguish between recommendations of which they are certain, and those where they are not. Existing confidence methods for RecSys are either inaccurate heuristics, conceptually complex or computationally very expensive. Consequently, real-world RecSys applications rarely adopt these methods, and thus, provide no confidence insights in their behavior.