视频个性化推荐方法可以分为基于内容的推荐、基于用户的推荐和基于社交网络的推荐三种。

常用的推荐方法包括协同过滤、基于内容的推荐、混合推荐等。其中,协同过滤是最常用的一种推荐方法,它基于用户历史行为(如观看记录、评分记录等)来推荐相似的视频;基于内容的推荐则是根据视频的元数据(如标题、标签、描述等)来推荐相似的视频;混合推荐则是将多种推荐方法结合起来使用,以提高推荐准确率。

受欢迎的推荐方法包括基于深度学习的推荐、基于图像识别的推荐等。其中,基于深度学习的推荐方法可以通过学习用户的历史行为和视频的内容特征来实现更准确的推荐;基于图像识别的推荐方法则可以通过分析视频的视觉特征来实现更精准的推荐。

以下是一些相关的文献网址:

  1. 'A Survey on Video Recommendation Techniques', https://www.researchgate.net/publication/331163709_A_Survey_on_Video_Recommendation_Techniques

  2. 'Deep Learning-Based Video Recommendation: A Review', https://ieeexplore.ieee.org/document/9054338

  3. 'A Hybrid Video Recommendation System Based on User Preferences and Video Content', https://www.mdpi.com/1424-8220/19/15/3261

  4. 'Personalized Video Recommendation Based on Multi-Source Data Fusion', https://www.sciencedirect.com/science/article/pii/S1364815218309297

  5. 'Video Recommendation Based on Social User Behavior and Content Analysis', https://dl.acm.org/doi/10.1145/3292500.3330670

  6. 'Image-Based Video Recommendation Using Convolutional Neural Networks', https://ieeexplore.ieee.org/document/8461236

  7. 'A Comparative Study of Video Recommendation Systems Based on Deep Learning Techniques', https://www.mdpi.com/2076-3417/10/23/8776/htm

  8. 'A Hybrid Video Recommendation System Using Deep Learning and Collaborative Filtering', https://www.sciencedirect.com/science/article/pii/S1877050920322564

  9. 'A Survey on Video Recommendation Systems Based on Deep Learning', https://www.sciencedirect.com/science/article/pii/S1877050919310819

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