A Convolutional Neural Network Based Sentiment Classification and the Convolutional Kernel Representation

机译：基于卷积神经网络的情感分类和卷积核表示

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摘要

This paper presents a multiple layer based convolutional neural network for sentiment analysis. Word embedding is present to learn the features and representations. This paper also presents a convolutional kernel representation for textual data. In order to evaluate the performance, this paper uses short-text corpus to evaluate. Experimental results show the feasibility of the approach.

机译：本文提出了一种基于多层的卷积神经网络进行情感分析。存在单词嵌入以学习特征和表示。本文还提出了用于文本数据的卷积核表示。为了评估性能，本文使用短文本语料库进行评估。实验结果表明了该方法的可行性。

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《International conference on applications of natural language to information systems》|2017年|287-291|共5页
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Shen Gao; Huaping Zhang; Kai Gao;
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关键词
Word embedding; Convolutional neural network; Classification; Sentiment analysis; Representation;

机译：词嵌入;卷积神经网络分类;情绪分析;表示;

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2. Combining attention-based bidirectional gated recurrent neural network and two-dimensional convolutional neural network for document-level sentiment classification [J] . Liu Fagui, Zheng Jingzhong, Zheng Lailei, Neurocomputing . 2020,第Jana2期

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3. Variable Convolution and Pooling Convolutional Neural Network for Text Sentiment Classification [J] . Dong Min, Li Yongfa, Tang Xue, Quality Control, Transactions . 2020,第期

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4. A Convolutional Neural Network Based Sentiment Classification and the Convolutional Kernel Representation [C] . Shen Gao, Huaping Zhang, Kai Gao International Conference on Applications of Natural Language to Information Systems . 2017

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5. Deep Neural Language Model for Text Classification Based on Convolutional and Recurrent Neural Networks [D] . Hassan, Abdalraouf. 2018

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A Convolutional Neural Network Based Sentiment Classification and the Convolutional Kernel Representation

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