随着网络技术和多媒体技术的发展，网络上教学资源的规模变得十分庞大，如何根据学习者的需要推荐其感兴趣的资源成为近年来研究的热点。然而，目前基于协同过滤的推荐算法较少考虑推荐用户与目标用户之间的信任关系，难以抵抗推荐用户的恶意推荐，无法保证推荐结果的可信性与精确度。针对这些问题，在传统协同过滤算法的基础上引入推荐者之间的信任关系，将传统协同过滤算法中的用户相似度与用户信任度进行线性加权组合，提出融合信任关系的协同过滤算法。仿真实验结果表明，与传统协同过滤推荐算法相比，该方法不仅提高了推荐的精确度，还能保证推荐结果的可信性，能更好地抵制恶意推荐。%With the development of network technology and multimedia technology, the scale of the teaching resources on the net-work becomes pretty large. How to recommend the resources to the learners according to the needs of the learners has become a hot issue in the recent years. However, because of the collaborative filtering recommendation algorithm taking the trust relation-ship between the users and target users so less, it is difficult to resist the recommendation of malicious users, and ensure the credibility and accuracy of the results. To solve the above problems, on the basis of traditional filtering algorithm, introducing the trust relationship between users into the algorithm, and combining the similarity of the traditional filtering algorithm with the trust degree in weighted linear method, we propose the title. The simulate experiment results show that, compared with the traditional collaborative filtering recommendation algorithm, the proposed method not only improves the accuracy of the recommendation, but also ensures the credibility of the results.
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