Research on The Application of Video Recommendation Algorithm Based on DeepFM

Heng Wei, Bo Gui
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Abstract

This paper studies the application of video recommendation algorithm based on DeepFM, studies the specific application of DeepFM algorithm in the field of video recommendation, and analyzes its performance. In this paper, the MovieLens video dataset is selected for experiments, and a simple video recommendation system is implemented by using UserCF, ItemCF and DeepFM. After recalling and sorting the dataset, the conclusion is drawn. The DeepFM model has superior performance in the sorting stage, and the loss is reduced by 0.55 % compared with the use of only FM model.
基于深度调频的视频推荐算法应用研究
本文研究了基于DeepFM的视频推荐算法的应用,研究了DeepFM算法在视频推荐领域的具体应用,并对其性能进行了分析。本文选择MovieLens视频数据集进行实验,利用UserCF、ItemCF和DeepFM实现了一个简单的视频推荐系统。通过对数据集的回顾和整理,得出结论。DeepFM模型在分类阶段表现优异,与仅使用FM模型相比,损失降低了0.55%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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