With the popularity of online learning platform, a large number of learning behavior data are generated. How to use big data mining technology to analyze online learning behavior, to solve the problem that learners often face “resource overload” and “learning confusion” , better implementation of teaching decision-making, learning process optimization, personalized learning method recommendation, etc., has become a research focus. Based on the learning behavior data of Suzhou online education center, this work studies the common recommendation system model. Combined with the data characteristics of the platform, a collaborative filtering recommendation algorithm based on knowledge map is proposed. With this algorithm, the accuracy of the platform’s recommended resources is more than 90%, which effectively solves the problem of “learning lost” for students.