Research on Text Emotion Analysis Method Based on Attention Mechanism and BGRU Network
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Guangjun Liu, Weiqing Yang, Lining Zhan, Xiangjun Li
The rapid development of the Internet makes social software such as e-commerce, major portals and other social software and new media emerge in endlessly, which has gradually become an important platform for people to exchange information and obtain information. Web text generally has the user's rich emotion, needs to carry on the data mining to these rich emotion, therefore this proposed to carry on the text emotion analysis research based on the attention mechanism and the double-door circular neural network model, is based on the two-way GRU emotion analysis algorithm model, unifies the emotion analysis character to carry on the algorithm optimization improvement, the improved algorithm model can enhance the Web text emotion analysis effect significantly.
Attention Mechanism, BGRU, Text Emotion