A Hidden Markov Model for Time-dependent Recommendation

Recommender systems are becoming progressively common and important in many areas to provide users with personalized recommendations.   This project is to predict users’ preferences for some items based on the rating data using a hidden Markov model.  EM algorithms will be used for the parameter estimation.