Recent recommender system user a method of combining collaborative filtering system and content based filtering system in order to slove the problem of the Sparsity and First-Rater in collaborative filtering system. In this paper, to make up for the prediction accuracy in hybrid Recommender system, the harmonic mean weight(CBCF_harmonic_mean) is used for calculating the user similarity weight. After setting up the threshold as 45 considering the performance of content based filtering, we apply significance weight of n/45 to user similarity weight. To estimate the performance of the proposed method, it if compared with that of combing both the existing collaborative filtering system and the content- based filtering system. As a result, it confirms that the suggested method is efficient at improving the prediction accuracy as solving problems of the exiting collaborative filtering system.