Chinese User Service Intention Classification Based on Hybrid Neural Network
TABLE IV: The results of various models working on the test set.
['[ITALIC] Models', 'Naive Bayes', 'Decision Tree', 'SVM']
In addition, we report the results of various models working on the test set. The method based on SVM has achieved better results than other traditional classification models, including Naive Bayes or Decision Tree based. However, the model based on the neural network has a better effect than the traditional machine learning classification models. The model based on CNN is better than that based on LSTM. It may be caused by that the sentences in this dataset are short, and the sequence order clutter caused by the colloquial problem is serious, these reasons are bad for the recurrent neural network to capture the temporal semantics.