Abstract: The area of collaborative filtering (CF) applied in IT project outsourcing is studied and the researches on personalized task recommendation are carried out. Based on this, a personalized task recommendation method is presented combined with Profile text similarity, task selection similarity and integrated similarity. This method transforms the users selection behavior into user items-class selection matrix, and it is used to compute the selection similarity among users. Users profile text similarity is also considered to balance the selection similarity, while integrated similarity is applied to measure the timeliness and values and build waiting recommendation item set by choosing the proper threshold. The experimental results indicate that the proposed method is effective and it could be used to alleviate the data sparseness and cold start problems.