We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Text Classification of Public Feedbacks using Convolutional Neural Network Based on Differential Evolution Algorithm.
- Authors
Zhang, S.; Chen, Y.; Huang, X. L.; Cai, Y. S.
- Abstract
Online feedback is an effective way of communication between government departments and citizens. However, the daily high number of public feedbacks has increased the burden on government administrators. The deep learning method is good at automatically analyzing and extracting deep features of data, and then improving the accuracy of classification prediction. In this study, we aim to use the text classification model to achieve the automatic classification of public feedbacks to reduce the work pressure of administrator. In particular, a convolutional neural network model combined with word embedding and optimized by differential evolution algorithm is adopted. At the same time, we compared it with seven common text classification models, and the results show that the model we explored has good classi- fication performance under different evaluation metrics, including accuracy, precision, recall, and F1-score.
- Subjects
ARTIFICIAL neural networks; DIFFERENTIAL evolution; COMPUTER algorithms; FEATURE extraction; ACCURACY
- Publication
International Journal of Computers, Communications & Control, 2019, Vol 14, Issue 1, p124
- ISSN
1841-9836
- Publication type
Article
- DOI
10.15837/ijccc.2019.1.3420