The selection of "Excellent Scientific Paper in the Field of Electronic Information (2022)" held by the Chinese Institute of Electronics is over. The article titled "A Text Sentiment Classification Modeling Method Based on Coordinated CNN-LSTM-Attention Model" won the award.
Authors
ZHANG Yangsen, ZHENG Jia, JIANG Yuru, HUANG Gaijuan and CHEN Ruoyu
Abstract
The major challenge that text sentiment classification modeling faces is how to capture the intrinsic semantic, emotional dependence information and the key part of the emotional expression of text. To solve this problem, we proposed a Coordinated CNNLSTM-Attention(CCLA) model. We learned the vector representations of sentence with CCLA unit. Semantic and emotional information of sentences and their relations are adaptively encoded to vector representations of document. We used softmax regression classifier to identify the sentiment tendencies in the text. Compared with other methods, the CCLA model can well capture the local and long distance semantic and emotional information. Experimental results demonstrated the effectiveness of CCLA model. It shows superior performances over several state-of-the-art baseline methods.
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