C-CNN-for-Chinese-Sentiment-Analysis

C-CNN-for-Chinese-Sentiment-Analysis

CarryChang

基于字符级卷积神经网络的细粒度的中文情感分析以及具体的应用，将顾客打分和评论情感进行两极映射，使用数据自动标注和基于弱监督预训练的数据增强方式自动扩充和优化数据集，实验证实了在情感分类中，使用本文的字符级卷积神经网络(C-CNN-SA)可以在不依赖分词的情况下，达到的精度和 F 值均高于词级粒度。并将模型上线使用，利用tensoflow+flask restful做出的后端服务化，具体的项目细节和讲解看右面的ppt

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51 Stars
14 Forks
51 Watchers
HTML Language
100 SrcLog Score
Cost to Build
$884.7K
Market Value
$1.29M
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8 data points  ·  2021-07-01 → 2026-04-01
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What is the CarryChang/C-CNN-for-Chinese-Sentiment-Analysis GitHub project? Description: "基于字符级卷积神经网络的细粒度的中文情感分析以及具体的应用，将顾客打分和评论情感进行两极映射，使用数据自动标注和基于弱监督预训练的数据增强方式自动扩充和优化数据集，实验证实了在情感分类中，使用本文的字符级卷积神经网络(C-CNN-SA)可以在不依赖分词的情况下，达到的精度和 F 值均高于词级粒度。并将模型上线使用，利用tensoflow+flask restful做出的后端服务化，具体的项目细节和讲解看右面的ppt". Written in HTML. Explain what it does, its main use cases, key features, and who would benefit from using it.

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