In order to solve the problem that data overload and data sparsity in collaborative filtering recommendation algorithm, the collaborative recommendation algorithm based on item factor analysis is proposed in this paper. The algorithm reduces the dimensions of item vector by use of factor analysis and gets some representative item factors, which are used to regression analysis of target items to forecast the evaluated items. Finally, experiments show that the algorithm is effective, which provides a new way for future recommendation algorithm research.