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一种用于社会化标签推荐的主题模型

DOI: 10.13190/j.jbupt.2014.03.008, PP. 38-42

Keywords: 社会化标签推荐,主题模型,标签主题粒度,噪声标签

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Abstract:

社会化标签中普遍存在标签的主题粒度和文档不一致以及部分标签和文档内容无关这两个问题,而现有基于主题模型的社会化标签推荐算法并没有同时对二者进行建模.针对这两点,提出了一种新的主题模型,该模型不仅允许标签和文档具有各自的主题粒度,而且允许标签来自与文档无关的噪声主题.在两个不同的社会化标签语料上的实验结果表明,所提出的模型相比内容相关模型和标签的隐含狄利克雷分配模型,在混淆度和平均正确率均值这两个指标上均有所提高.

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