Deep Keyphrase Generation
Table 3: Absent keyphrases prediction performance of RNN and CopyRNN on five datasets
['[BOLD] Dataset', '[BOLD] RNN  [BOLD] R@10', '[BOLD] RNN  [BOLD] R@50', '[BOLD] CopyRNN  [BOLD] R@10', '[BOLD] CopyRNN  [BOLD] R@50']
This indicates that, to some extent, both models can capture the hidden semantics behind the textual content and make reasonable predictions. In addition, with the advantage of features from the source text, the CopyRNN model also outperforms the RNN model in this condition, though it does not show as much improvement as the present keyphrase extraction task. Note that the term “indexing” does not appear in the text, but the models may detect the information “index videos” in the first sentence and paraphrase it to the target phrase. And the CopyRNN successfully predicts another two keyphrases by capturing the detailed information from the text (highlighted text segments).