Keyphrase Extraction with Span-based Feature Representations
Table 5: We conduct experiment using RNN word representation based Span Keyphrase Extraction classification model named SKE-RNN-Cls. SKE-RNN-Cls achieves 1.8% and 12.9% improvements over CopyRNN on F1@5 and F1@10 respectively.
['[BOLD] Method', '[BOLD] KP20K  [BOLD] F1 [BOLD] @5', '[BOLD] KP20K  [BOLD] F1 [BOLD] @10']
We compared this model with CopyRNN on the largest test dataset SKE-RNN-Cls achieves 1.8% and 12.9% improvements over CopyRNN on F1@5 and F1@10 respectively.