Short Text Classification with A Convolutional Neural Networks Based Method
Yibo Hu, Yang Li, Tao Yang, Quan Pan · 2018
The traditional machine learning algorithms are easily affected by datasets in short text classification tasks, so they have weak generalization ability when confronted with new situations. This paper presents a new method SVMCNN by combining Convolutional Neural Networks and Support Vector Machine. Training the SVMCNN model with labeled datasets, and using the collected Twitter data for classification test. The results show that the SVMCNN, especially pre-trained SVMCNN has good performance in short text classification, which gets the high Precision rate, Recall rate and F1-measure.