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Application of SVD technology in video recommendation system

机译:SVD技术在视频推荐系统中的应用

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The most direct access to evaluate what kinds of topics are valuable for video producers, and bring them inspiration is to seek subjects which specific groups concern currently. We can obtain massive user information from social networking platforms, large video sites and search engines, and then exploit the data to produce more practical works with the combination of business requirements. In views of the existing disadvantages of inferior scalability, sparsity problem and huge volume test data, the application of Singular Value Decomposition Method(SVD) actualize the unknown prediction score function of set of tests. The simulation results show that scalability, sparsity and omputational efficiency improved effectively.
机译:评估哪种主题对视频制作者有价值的最直接途径是,寻找特定群体当前关注的主题,从而为他们带来灵感。我们可以从社交网络平台,大型视频站点和搜索引擎获取大量的用户信息,然后利用这些数据结合业务需求来生成更实用的作品。针对可伸缩性差,稀疏性和测试数据量大的缺点,奇异值分解法(SVD)的应用实现了测试集的未知预测得分函数。仿真结果表明,可扩展性,稀疏性和计算效率得到了有效提高。

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