DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
Table 3: F1 score (%) comparison only for aspect term extraction.
['[BOLD] Model', 'SL', 'SR', 'ST']
Results on ATE. DE-CNN is the current state-of-the-art model on ATE as mentioned above. Comparing with it, DOER achieves new state-of-the-art scores. DOER∗ denotes the DOER without ASC part. As the table shows, DOER achieves better performance than DOER∗, which indicates the interaction between ATE and ASC can yield better performance for ATE than only conduct a single task.