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A matrix-based feature vector definition and a SVM-BDT-based classification system for classifying nursing-care texts

机译:基于矩阵的特征向量定义和基于SVM-BDT的护理文本分类系统

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In this paper, we propose a method of nursing-care text classification. We have proposed some nursing-care classification methods using fuzzy systems, standard three-layer neural networks, and support vector machines. Also we have proposed several types of feature vector definitions for expressing free style Japanese texts into numerical vectors. This paper proposes a novel feature vector definition and a support vector machine utilizing a decision tree (SVM-BDT) based classification system. From experimental results, the effectiveness of both feature definition and SVM-BDT-based classification system is shown.
机译:在本文中,我们提出了一种护理文本分类方法。我们提出了一些使用模糊系统,标准三层神经网络和支持向量机的护理分类方法。此外,我们提出了几种类型的特征向量定义,用于将自由风格日语文本表达到数字向量中。本文提出了一种利用基于决策树(SVM-BDT)的分类系统的新颖特征向量定义和支持向量机。从实验结果,显示了特征定义和基于SVM-BDT的分类系统的有效性。

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