Calibrate Recommendations: Calibrates recommendations across topics based on the users historical propensity to choose

Haven't read the paper yet, but seems like a very simple idea. If historically user watched 70% horror movies and 30% romance than 70% of recommendations should be horror movies. Ranking systems might be overly biased towards the highest propensity to choose type item