Personalized recommendation can hide information on the depth of excavation, to obtain users information that users can not obtain by the information retrieval results. Because intelligent and humane personalized service, maNing it application area more and more widely, recommend the use of technology has become even more and more reasonable. Paper presents a library of personalized recommendation service based on user-tiered strategy. The experimental results show that the proposed methods and strategy are effective.