2017 Volume 19 Issue 2 Pages 13-19
In previous research of recommender system Markov decision processes are used in order to represent recommender system. Total reward is maximized with reference to a Bayes criterion. In the previous research a questionnaire method for a new customer is not studied. In other previous research a questionnaire method for a new customer is studied, but the total reward is not maximized.
In this research we apply Markov decision processes to questionnaire for a new customer in recommender system. We propose a new questionnaire method which maximizes the total reward with reference to the Bayes criterion. In the proposed method dynamic programming is used.
