The user interests models in the existing recommendation systems can express the user’s interests effectively
but they can’t update the user interests models in time while the user interests change. This paper proposes a recommendation system of messages depending on user’s feedback to modify user interests. It can update model and the feature vector in time
and then the most matching recommendation results for every user. In addition
the system can better adapt to the growth of the scale of data by using HBase(Hadoop Database) as storage.