Aspect-Based Sentiment Analysis on Laptop14
82.86AccuracyOTESGN
Evaluation results
| Method | Links | ||
|---|---|---|---|
| OTESGN2025.09 | 82.86 | 80.52 | |
| RDGCN (2024)2025.09 | 82.12 | 78.29 | |
| CSADGCN (2024)2025.09 | 82.12 | 79.22 | |
| HPEP-GCN (2025)2025.09 | 81.96 | 79.1 | |
| YORO (2024)2025.09 | 81.82 | 78.32 | |
| DualGCN (2021)2025.09 | 81.8 | 78.1 | |
| SVCCL (2025)2025.09 | 81.35 | 77.76 | |
| KDGN (2023)2025.09 | 81.32 | 77.59 | |
| LWEDA-ACT (2025)2025.09 | 81.17 | 78.29 | |
| IDGNN (2024)2025.09 | 81.12 | 78.46 | |
| APSCL (2023)2025.09 | 81.02 | 78.47 | |
| SSEGCN (2022)2025.09 | 81.01 | 77.96 | |
| CADA (2025)2025.09 | 80.88 | 77.71 | |
| BERT (2019)2025.09 | 79.91 | 76 | |
| DGEDT (2020)2025.09 | 79.8 | 75.6 | |
| TNet (2018)2025.09 | 76.54 | 71.75 | |
| ASGCN (2019)2025.09 | 75.55 | 71.05 | |
| RAM (2017)2025.09 | 74.49 | 71.35 |