计算机科学 ›› 2015, Vol. 42 ›› Issue (11): 96-100.doi: 10.11896/j.issn.1002-137X.2015.11.020
纪淑娟,王 理,梁永全,赵建立
JI Shu-juan, WANG Li, LIANG Yong-quan and ZHAO Jian-li
摘要： 在未来的智能电视系统中,真正的智能视频推荐应该是不需要用户评分动作就能自动、准确地获得用户兴趣、爱好并做出推荐的系统。研究无评分动作约束下的用户评分(揭示了他们的兴趣和爱好)自动获取技术是真正的智能推荐必须解决的一个关键问题。给出了一种基于神经网络的用户视频隐性评分自动获取方法。基于用户视频观看行为与评分样本的实验结果表明,该方法可以有效地获取用户的隐性评分信息。
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