Table 6.
Performance of involved topic modeling methods with a different number of features f, f = 10, 100, 1,000, and 10,000 (average value of recall, precision, and F-score).
| TM method | Number of features | |||
|---|---|---|---|---|
| 10 | 100 | 1,000 | 10,000 | |
| F-score | F-score | F-score | F-score | |
| LSA | 0.108238987 | 0.177539633 | 0.196284973 | 0.187135878 |
| LDA | 0.118222579 | 0.313004427 | 0.596767795 | 0.616768865 |
| NMF | 0.124100619 | 0.246607097 | 0.384831984 | 0.478534632 |
| PCA | 0.118742505 | 0.273855576 | 0.459150019 | 0.553060479 |
| RP | 0.123841731 | 0.101052719 | 0.126599635 | 0.114772128 |
Bold values represent the highest performance results.