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Probabilistic Relational Models with Relational Uncertainty: An Early Study in Web Page Classification

机译:具有关系不确定性的概率关系模型:网络页面分类的早期研究

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In the last decade, new approaches focused on modelling uncertainty over complex relational data have been developed. In this paper one of the most promising of such approaches, known as Probabilistic Relational Models (PRMs), has been investigated and extended in order to measure and include uncertainty over relationships. Our extension, called PRMs with Relational Uncertainty, has been evaluated on real-data for web document classification purposes. Experimental results shown the potentiality of the proposed methods of capturing the real “strength” of relationships and the capacity of including this information into the probability model.
机译:在过去的十年中,已经开发出了专注于在复杂关系数据上建模不确定性建模的新方法。在本文中,已经研究并扩展了被称为概率关系模型(PRMS)的这种方法中最有希望的,以便测量并包括对关系的不确定性。我们的扩展名为PRMS,具有关系不确定性,已在Web文档分类目的的实际数据上进行评估。实验结果表明了捕获关系的真实“力量”的潜力以及将该信息包含在概率模型中的能力。

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