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Semantic conceptual primitives computing in text classification

机译:文本分类中的语义概念图元计算

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This paper presents a method for enhancing text classification performance with semantic computing. It adopts conceptual primitives with semantic relations as knowledge expression. Based on the semantic expression, it mined the association relation of primitives among different text classification, and these association rules take association relation as text classification feature. The presented method not only considers what kind of the semantic primitives that a text contains, but also takes account of the association relation of the semantic primitives. Moreover, we test the method with public text classification text set. The experiment result shows that, comparing with the commonly used methods, this method prompts text classification performance.
机译:本文提出了一种通过语义计算提高文本分类性能的方法。它采用具有语义关系的概念原语作为知识表达。基于语义表达,挖掘了不同文本分类之间原语的关联关系,这些关联规则将关联关系作为文本分类特征。所提出的方法不仅考虑了文本包含什么样的语义原语,还考虑了语义原语的关联关系。此外,我们使用公共文本分类文本集测试该方法。实验结果表明,与常用方法相比,该方法具有较高的文本分类性能。

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