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Using Bag-of-Concepts to Improve the Performance of Support Vector Machines in Text Categorization

机译:使用概念袋来提高文本分类中支持向量机的性能

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This paper investigates the use of concept-based representations for text categorization. We introduce a new approach to create concept-based text representations, and apply it to a standard text categorization collection. The representations are used as input to a Support Vector Machine classifier, and the results show that there are certain categories for which concept-based representations constitute a viable supplement to word-based ones. We also demonstrate how the performance of the Support Vector Machine can be improved by combining representations.
机译:本文调查了基于概念的文本分类的表示。我们介绍了一种创建基于概念的文本表示的新方法,并将其应用于标准文本分类集合。表示将表示作为支持向量机分类器的输入,结果表明,基于概念的表示构成了基于Word的概念的某些类别。我们还通过组合表示,展示如何通过组合表示来改善支持向量机的性能。

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