| 基于深度学习的IPTV视频用户行为分析方法研究 |
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| 引用本文： | 刘超,贾毓臻,王攀. 基于深度学习的IPTV视频用户行为分析方法研究[J]. 计算机应用与软件, 2019, 36(6): 167-170,286 |
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| 作者姓名： | 刘超 贾毓臻 王攀 |
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| 作者单位： | 江苏大学电气信息工程学院 江苏镇江212013;南京邮电大学现代邮政研究院 江苏南京210003 |
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| 基金项目： | 中国博士后科学基金;江苏大学高级人才科研启动基金 |
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| 摘 要： | IPTV视频业务的复杂性和多样性使其难以充分发挥运营商技术优势。借助深度神经网络DNN模型对IPTV视频用户进行用户行为分析。利用深度学习算法对用户点播视频活跃度实施精确分类,从而帮助IPTV服务提供商合理配置资源,同时为终端用户提供更高效优质的服务。实验结果表明,与现有的方法相比,该方法收敛快,分类准确率达93%。
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| 关 键 词： | IPTV用户行为 深度学习 DNN |
IPTV VIDEO USER BEHAVIOR ANALYSIS METHOD BASED ON DEEP LEARNING |
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| Liu Chao,Jia Yuzhen,Wang Pan. IPTV VIDEO USER BEHAVIOR ANALYSIS METHOD BASED ON DEEP LEARNING[J]. Computer Applications and Software, 2019, 36(6): 167-170,286 |
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| Authors: | Liu Chao Jia Yuzhen Wang Pan |
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| Affiliation: | (School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, Jiangsu, China;Modern Postal Research Institute, Nanjing Posts and Telecommunications University, Nanjing 210003, Jiangsu, China) |
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| Abstract: | In view of the complexity and diversity of IPTV video services,it is difficult to give full play to the technical advantages of operators.In this paper,the user behavior of IPTV video users was analyzed by means of deep neural network model.The deep learning method was used to accurately classify the user s on-demand video activity,thereby helping the IPTV service provider to properly allocate resources and provide more efficient and high-quality services for the end users.The experimental results show that compared with the existing methods,the method converges quickly and the classification accuracy rate is 93%. |
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| Keywords: | IPTV user behavior Deep learning DNN |
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