Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNN
Table 6: Best results for our attention-RNNs on AE on the Restaurants dataset.
['[BOLD] Embeddings', '[BOLD] |d|', '[BOLD] |cw|', '[BOLD] |h|', '[BOLD] F1']
All of our best performing models use a bidirectional architecture. In fact, bidirectionality provided an average significant absolute gain of 0.89 F1-score (p=1.25×10−17). Additionally, using CoreNLP as preprocessing pipeline provided an average gain of 0.585 F1-score (p=2.98×10−21) over Senna.