Research Article
A Performance Comparison of Unsupervised Techniques for Event Detection from Oscar Tweets
Table 4
Topic recall, keyword precision, and keyword recall of all the methods.
| Methods | Number of topics | Topic recall | Keyword precision | Keyword recall |
| LDA | 5 | 0.6 | 1 | 0.6 | K-SVD | 5 | 0.8 | 1 | 1 | Doc-p | 5 | 1 | 1 | 1 | Feat-p | 5 | 0.6 | 0.8 | 0.6 | SFPM | 5 | 1 | 1 | 1 |
| LDA | 10 | 0.8 | 0.7 | 0.7 | K-SVD | 10 | 0.8 | 0.8 | 0.8 | Doc-p | 10 | 0.8 | 1 | 0.8 | Feat-p | 10 | 0.7 | 0.7 | 0.6 | SFPM | 10 | 0.8 | 0.9 | 0.8 |
| LDA | 15 | 0.5 | 0.7 | 0.5 | K-SVD | 15 | 0.7 | 0.8 | 0.7 | Doc-p | 15 | 0.5 | 0.9 | 0.5 | Feat-p | 15 | 0.5 | 0.7 | 0.5 | SFPM | 15 | 0.8 | 0.9 | 0.8 |
| LDA | 20 | 0.6 | 0.6 | 0.5 | K-SVD | 20 | 0.7 | 0.8 | 0.6 | Doc-p | 20 | 0.6 | 0.8 | 0.5 | Feat-p | 20 | 0.6 | 0.6 | 0.5 | SFPM | 20 | 0.8 | 0.9 | 0.8 |
| LDA | 25 | 0.5 | 0.5 | 0.4 | K-SVD | 25 | 0.6 | 0.7 | 0.5 | Doc-p | 25 | 0.5 | 0.5 | 0.5 | Feat-p | 25 | 0.5 | 0.5 | 0.4 | SFPM | 25 | 0.7 | 0.7 | 0.6 |
|
|