Abstract
Collaborative filtering is to calculate the similarity between users by taking all the preferences of a user as a reference value. After finding adjacent users, the information mining of relevant recommendations can be realized through similar behavior history. This paper proposes a Chinese character recommendation algorithm based on user collaborative filtering technology by digging deeply into the recorded information of students’ Chinese character learning.
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