Recommendation system with active learning
One way to approach recommendation systems that can change over time based on user input is to model them with Reinforcement Learning. There is an inherent notion of time and active choices with Reinforcement Learning.
Contextual-Bandit is a popular approach that models information about the user (context) to influence which options (arms of the bandit) are shown to a user.