| Title | Auto-classification of Government Department-specific News Articles |
|---|---|
| ID_Doc | 79231 |
| Authors | Lee, SM; Ryu, SE; Ahn, SJ |
| Title | Auto-classification of Government Department-specific News Articles |
| Year | 2019 |
| Published | |
| Abstract | The purpose of this study is to propose an unsupervised learning-based method for automatic classification of news articles usilig a dictionary, mcorporatiiig the attributes of each admmistrative department. The results of auto-classification of news articles for individual departments showed 71% accuracy. A classification technique using unsupervised learning may be utilized to automatically classify documents without labels when gathering policy issues for individual administrative departments. |
No similar articles found.