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基于社会化标签多维去噪的音乐推荐方法

Music Recommendation Method Based on Social Tags Multidimensional Denoising
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摘要 音乐推荐系统面临的主要是推荐的准确性、多样性以及信息的缺失、噪音等问题。社会化标签中包含了丰富的用户描述的信息以及项目内容信息,基于社会化标签可以提供更准确的推荐,但是大量的标签带有噪音,采用多维对应分析删除标签中的噪音,利用"用户-项目-社会化标签"两两之间的联系建立带权重标签的用户兴趣模型,将标签权重高的资源向用户推荐。实验表明,该方法能满足用户个性化音乐需求。 In this paper,Multidimensional Correspondence Analysis is applied to delete the noise in tags and the user interest model with weight label is established based on the user-resources-social tags.Items with high weight tags could be recommended.Experiments show that users＂ personalized music demand could be meet by present methods.
作者 姚谊 吴卿 武国平 沈渊锋
机构地区 杭州电子科技大学计算机学院
出处 《工业控制计算机》 2016年第6期118-120,122,共4页 Industrial Control Computer
关键词 音乐推荐 社会化标签 多维对应分析 个性化 music recommendation,social tags,many dimensions correspondence analysis,personalization
分类号 TP391.3 [自动化与计算机技术—计算机应用技术]
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参考文献12

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工业控制计算机
2016年 第6期

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