A Lightweight Method for Modeling Confidence in Recommendations with Learned Beta Distributions

Understand

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.