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    Sentiment Classification Based on Piecewise Pooling Convolutional Neural Network

    Yuhong Zhang1,*, Qinqin Wang1, Yuling Li1, Xindong Wu2

    CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 285-297, 2018, DOI: 10.3970/cmc.2018.02604

    Abstract Recently, the effectiveness of neural networks, especially convolutional neural networks, has been validated in the field of natural language processing, in which, sentiment classification for online reviews is an important and challenging task. Existing convolutional neural networks extract important features of sentences without local features or the feature sequence. Thus, these models do not perform well, especially for transition sentences. To this end, we propose a Piecewise Pooling Convolutional Neural Network (PPCNN) for sentiment classification. Firstly, with a sentence presented by word vectors, convolution operation is introduced to obtain the convolution feature map vectors. Secondly, More >

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