Research on Emotion Recognition Model of Takeaway Evaluation Text Based on LSTM-CNN

Ruiqing Gao

doi:10.54097/ajst.v7i2.12262

Authors

Ruiqing Gao

DOI:

https://doi.org/10.54097/ajst.v7i2.12262

Keywords:

LSTM-CNN, Takeaway, Evaluation Text, Emotion Recognition.

Abstract

Takeaway evaluation is a literal evaluation of the products and services experienced by consumers, which not only provides a realistic basis for the improvement of products and services of merchants, but also affects the purchase decision of consumers in the future. In this paper, NLP(natural language processing) is used for preprocessing in tensorflow environment, and an emotion recognition model of takeaway evaluation text based on LSTM-CNN is established. The model is based on Bi-LSTM and attention mechanism, and uses Word2Vec method to vectorize text vocabulary. Then, the LSTM-CNN serial hybrid model is used to extract the context and local semantics of the text, and the effectiveness of the algorithm is verified by an example. The precision reaches 0.937, the recall rate reaches 0.896,F1 and the F1 value reaches 0.906. Through horizontal comparison, it can be found that the model in this paper is outstanding in this task, and the emotion enhancement model also improves the classification accuracy to some extent.

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