A matrix-based feature vector definition and a SVM-BDT-based classification system for classifying nursing-care texts
A matrix-based feature vector definition and a SVM-BDT-based classification system for classifying nursing-care texts
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DOI：
10.1109/fuzz-ieee.2015.7337976
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发表时间：
2015-08
期刊：
影响因子：
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通讯作者：
M. Nii;Kazunobu Takahama;A. Uchinuno;R. Sakashita
中科院分区：
文献类型：
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作者：
M. Nii;Kazunobu Takahama;A. Uchinuno;R. Sakashita
本文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，我们还提出了几种类型的特征向量定义，用于将自由式日语文本表示为数字向量。本文提出了一种新的特征向量定义和基于决策树（SVM-BDT）分类系统的支持向量机。实验结果表明，特征定义和基于svm - bdt的分类系统都是有效的。
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.