In this paper, we propose a novel ranking function learning framework based on relevance propagation. The propagation process is used to propagate the relevance scores from labeled documents to other unlabeled ones so that more training data are available to learn the ranking function. It is realized by the manifold ranking algorithm, which has been proved to be very effective in content-based ...