Abstract:The advent of the era of the Internet causes the “excessive” of knowledge dissemination, knowledge fragment and disorganization makes users who have requirements of a systematic study difficult to know how to start. How to realize personalized knowledge recommendation for users is one of the key problems to be solved in the intelligent library system. This paper uses the context preference extraction technology to obtain the users' interest. And it introduces weighted factor based on the intelligent library system as an example in the user-based collaborative filtering recommendation algorithm and the collaborative filtering recommendation algorithm, it better solves “cold start” in the recommendation to new users as, implements the service of personalized recommendation results.