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Personalized Learning Resources Recommendation Model Based on Transfer Learning

机译:基于转移学习的个性化学习资源推荐模型

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This paper based on the traditional learning resources of collaborative-filtering personalized recommendation systems exist sparse and cold start is put forward based on the personal learning resources study migration recommend model, study method can move from existing data transfer knowledge, to help the new knowledge in the future study. E-Learning environment, use of knowledge transfer for learners to provide the study resources recommended. And in a certain degree of collaborative-filtering solve sparse solution and cold start-up problem.
机译:本文基于传统的协作过滤个性化推荐系统学习资源稀疏存在和冷启动的基础上,提出了基于个人学习资源的学习迁移推荐模型,研究方法可以从现有的数据转移知识转移,以帮助新知识的发展。未来的研究。在电子学习环境中,利用知识转移为学习者提供推荐的学习资源。并在一定程度上通过协同过滤解决了稀疏解和冷启动问题。

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