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Web Page Classification: A Probabilistic Model with Relational Uncertainty

机译:网页分类:具有关系不确定性的概率模型

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摘要

In this paper we propose a web document classification approach based on an extended version of Probabilistic Relational Models (PRMs). In particular PRMs have been augmented in order to include uncertainty over relationships, represented by hyperlinks. Our extension, called PRM with Relational Uncertainty, has been evaluated on real data for web document classification purposes. Experimental results shown the potentiality of the proposed model of capturing the real semantic relevance of hyperlinks and the capacity of embedding this information in the classification process.
机译:在本文中,我们提出了一种基于扩展关系型概率模型(PRM)的Web文档分类方法。特别地,已增加了PRM,以包括由超链接表示的关系的不确定性。我们的扩展名为具有关系不确定性的PRM,已针对Web文档分类目的对真实数据进行了评估。实验结果表明,所提出的模型能够捕获超链接的真实语义相关性,并能够在分类过程中嵌入该信息。

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