Abstract: With the Internet technology and modern E-commerce becoming popular, the recommender system has been widely used, but two problems of most recommendation algorithms still remain, i.e. cold start and explanatory problem. Based on the HFT (Hidden Factors and Hidden Topics) model which combines the review and rating information, an improved HFT model is proposed. By adding the free vector in order to capture the review information not discussed in the HFT model, the two problems can be released and the model accuracy improved. At last, the two large datasets shows that the proposed model is better than the HFT model in accuracy, which can largely benefit the use of review information.

Key words: recommender system, improved HFT model, review text, free vector