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As science and technology continue to advance, artificial intelligence technology is progressively being applied in diverse fields, among which the development of online learning platform has become a convenient way for people to obtain knowledge. With the theme of ^ Research on Intelligent Recommendation Algorithm of online learning Platform based on Artificial Intelligence ^, this research is devoted to explore how to improve the user experience of online learning platform through advanced artificial intelligence technology. With the popularity of online learning, the problems of information overload and difficulty in course selection are becoming more and more prominent. In order to solve this problem, we introduce intelligent recommendation algorithm, which aims to provide personalized and efficient learning resource recommendation for each learner through the powerful learning and analysis ability of artificial intelligence. The core idea of this research is to comprehensively analyze learners' historical learning behavior, interest preference and subject level through artificial intelligence technologies such as deep learning and data mining. Based on this information, we built an intelligent recommendation system that can accurately predict the needs of learners and recommend the courses, textbooks and learning resources that best fit the personalized learning trajectory. In our research, we employ advanced algorithms such as deep neural networks to model and train large amounts of learning data. Through these algorithms, we can dig out the potential learning patterns and rules, and tailor the most suitable learning path for each learner. The research results show that the intelligent recommendation algorithm of online learning platform based on artificial intelligence has achieved remarkable results in improving the recommendation accuracy.
Kuangye Song (Tue,) studied this question.
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