I have a music recommender system with implicit ratings on Apache Spark with MLlib, CF and ALS. I have several ways of how I get preference matrix from raw events data.
Now I just count how many times each user played each song. But I want rating to decrease with time after last song playing. I assumed two strategies: rating decline linearly and hyperbolic with days after last event.
How can I evaluate these two strategies offline on raw data without A/B testing or similar techniques that involve user interaction? How can I make an approximation for parameters?