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Nursing-care text classification using word vector representation and convolutional neural networks

机译:基于词向量表示和卷积神经网络的护理文本分类

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In this paper, we propose a convolutional neural network (CNN) based classification method for nursing-care classification. CNNs have obtained strong performance in computer vision speech recognition areas. Recently, CNNs have been also applied sentence classification. We have studied nursing-care text classification [6]-[18]. In our former works, we proposed several types of feature definitions and examined some classification models. In this paper, each text is represented as a concatenated word vector. Then, every text is classified using CNN-based classification methods. We examined some classification models at the classification layer in CNNs. From our experimental results, the proposed CNN-based method obtained better performance than our former works.
机译:在本文中,我们提出了一种基于卷积神经网络(CNN)的护理分类方法。 CNN在计算机视觉语音识别领域获得了出色的表现。最近,CNN也已应用于句子分类。我们研究了护理文本分类[6]-[18]。在我们以前的作品中,我们提出了几种类型的特征定义并检查了一些分类模型。在本文中,每个文本都表示为级联词向量。然后,使用基于CNN的分类方法对每个文本进行分类。我们在CNN的分类层中检查了一些分类模型。从我们的实验结果来看,提出的基于CNN的方法比我们以前的工作获得了更好的性能。

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