From the PRP to the Low Prior Discovery Recall Principle for Recommender Systems

Rocío Cañamares, Pablo Castells

Abstract: We revisit the Probability Ranking Principle in the context of recommender systems. We find a key difference in the retrieval protocol with respect to query-based search, that leads to the identification of different optimal ranking principles for discovery-oriented recommendation. Based on this finding, we revise the effectiveness of common non-personalized ranking functions in respect to the new principles. We run an experiment confirming and illustrating our theoretical analysis, and providing further observations and hints for reflection and future research.