Abstract
This paper implements the design of knowledge push system by the aid of machine learning, and details the key technologies including feature extraction of user data, method of constructing and updating user interest model, and the recommendation algorithm. By constructing the knowledge push model, knowledge resources can be pushed to users automatically and accurately, which can reduce the cost of knowledge retrieval and promote the knowledge sharing and reuse.
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