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Research on Collaborative Filtering Personalized Recommendation Algorithm Based on Deep Learning Optimization

机译:基于深度学习优化的协作滤波个性化推荐算法研究

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摘要

In order to improve the accuracy of the project in the recommendation process, the article compares the existing content-based and collaborative filtering recommendation calculations, makes full use of the advantages of different algorithms, and proposes a collaborative filtering personalized recommendation algorithm based on deep learning optimization. Through the deep learning training of users' preferences, the corresponding parameters are adjusted to establish a personalized recommendation method. Through experimental verification, the proposed algorithm can effectively improve the quality of personalized recommendation.
机译:为了提高项目的准确性,在推荐过程中,该文章比较了现有的基于内容和协作过滤推荐计算,充分利用了不同算法的优点,并提出了一种基于深度学习的合作滤波个性化推荐算法优化。通过用户偏好的深度学习培训,调整相应的参数以建立个性化推荐方法。通过实验验证,所提出的算法可以有效提高个性化推荐的质量。

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