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Effective XML Classification Using Content and Structural Information via Rule Learning

机译:通过规则学习使用内容和结构信息进行有效的XML分类

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We propose a new approach to XML classification, that uses a particular rule-learning technique for the induction of interpretable classification models. These separate the individual classes of XML documents by looking at the presence within the XML documents themselves of certain features, that provide information on their content and structure. The devised approach induces classifiers with outperforming effectiveness in comparison to several established competitors.
机译:我们提出了一种XML分类的新方法,该方法使用一种特殊的规则学习技术来归纳可解释的分类模型。这些通过查看XML文档本身中某些功能的存在来分离XML文档的各个类,这些功能提供有关其内容和结构的信息。与几个已建立的竞争者相比,该设计方法可以诱使分类器具有超乎寻常的效果。

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