The Hidden Dimension of Relevance: How Price Shapes Recommender Outcomes

In most recommender systems, the primary objective is to surface the most relevant items to users eg : restaurants, dishes, movies, products that they are most likely to purchase. Optimizing for relevance makes practical sense as it aligns with engagement metrics like conversion rate ( CVR ) or click through rate ( CTR ). But […] The post The Hidden Dimension of Relevance: How Price Shapes Recommender Outcomes appeared first on IEEE Computer Society.