The invention discloses a method and a system for core process knowledge intelligent pushing based on multi-model fusion. The method comprises: preprocessing existing corpus data, and then inputting the data into a classification algorithm model for pre-classification, improving effect of classification through model fusion, when user queries or user feeds back, performing similarity calculation on user input and text categories, to determine the categories to which keywords belong, taking first k1 most similar categories, just retrieving in the categories, for each category, using the input keywords to retrieve respectively using different models in the category, combining all previous results, performing relevancy sorting using a BM25 algorithm, taking first k2 results, and using Jaccardsimilarity to remove texts which are too similar in the results, finally, returning the results to users. The method and the system can further adjust user's keyword models according to the feedbackof the users, and better fit needs of the users, so as to optimize user pushing effect and matching degree in the next pushing.