Research and Application of User Behavior Data Analysis Technology for E-commerce
, e
27 feb 2025
INFORMAZIONI SU QUESTO ARTICOLO
Pubblicato online: 27 feb 2025
Ricevuto: 25 set 2024
Accettato: 23 gen 2025
DOI: https://doi.org/10.2478/amns-2025-0116
Parole chiave
© 2025 Xiaohan Yuan et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1.
Figure 2.
Figure 3.
Figure 4.
Figure 5.
Figure 6.
Figure 7.
Figure 8.
Figure 9.
Figure 10.
Comparison of effects of three models
| Model Name | Accuracy rate | Recall rate | F1 Value |
|---|---|---|---|
| Logistic regression | 4.25% | 4.31% | 4.27% |
| LightGBM | 5.61% | 5.63% | 5.62% |
| LightGBM + LR | 5.81% | 602.70% | 5.93% |
Evaluation indicators of each algorithm
| Precision | Coverage | MAE | Diversity | Surprise | Unexpectedness | |
|---|---|---|---|---|---|---|
| 16.68% | 8.34% | 89.11% | 0.365 | 10.956 | 8.841 | |
| 23.94% | 99.20% | 78.68% | 0.914 | 8.130 | 1.633 | |
| 26.40% | 99.20% | 76.93% | 0.936 | 8.242 | 1.444 |
Overall prediction results
| Model Name | Accuracy rate | Recall rate | F1 |
|---|---|---|---|
| Logistic regression | 4.66% | 4.72% | 4.68% |