In this paper, a multi feature fusion clustering algorithm based on the Q&A community is presented, which to extract the candidate label by performing clustering on the Q-A pairs. It is proposed to combine TF/IDF, context information entropy, word length as feature to extract, select and score keywords. The experiment not only confirms effectiveness the compared with the traditional system, but also validates the precision of the multi feature fusion model.