Deep learning sentiment analysis model based on semantic enhancement and analysis method thereof
A sentiment analysis and deep learning technology, applied in the fields of natural language processing and deep learning, which can solve complex problems
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[0048] The present invention will be described in further detail below in conjunction with the accompanying drawings.
[0049] A deep learning sentiment analysis model based on semantic enhancement, such as figure 1 As shown, the model is composed of six layers, which are word embedding layer, emotion semantic enhancement layer, CNN convolution sampling layer, pooling layer, LSTM layer, emotion classification layer from bottom to top; the word embedding layer will The words of the sentence are converted into low-dimensional word vectors; the emotional semantic enhancement layer is used to enhance the emotional semantics of the model; the CNN convolution sampling layer is used to automatically extract word features; the pooling layer is used to reduce the dimension of the feature vector ; The LSTM layer is used to capture the long-distance dependencies in the sentence, and remember the long-term dependent serialized information; the emotion classification layer uses Softmax for...
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