The general image aesthetic research can not represent the user’s personalized aesthetic preferences becaused it does not consider the aesthetic differences among users. In order to represent the user’s personalized aesthetic preferences more effectively, a user aesthetic representation construction method based on personalized generation template aggregation using the Counting Grid model was proposed in this research. It constructs a more compact user image aesthetic representation vector, which can better describe the user characteristics. Experimental results show that the way of user aesthetic representation constructed by the proposed method can obtain higher recognition rate in user identification, and can also obtain more realistic recommendation results in user recommendation.