Deep Keyphrase Generation
Table 4: Keyphrase prediction performance of CopyRNN on DUC-2001. The model is trained on scientific publication and evaluated on news.
['[BOLD] Model  [BOLD] Tf-Idf', '[BOLD] F1 0.270', '[BOLD] Model  [BOLD] ExpandRank', '[BOLD] F1 0.269']
We use the popular news article dataset DUC-2001 Wan and Xiao The dataset consists of 308 news articles and 2,488 manually annotated keyphrases. The performance of CopyRNN is better than TextRank Mihalcea and Tarau It is worth noting that the hyperparameters of baseline models, such as number of recalled keyphrases for Tf-Idf and SingleRank, are carefully tuned and may drastically affect the results. However for CopyRNN we simply report its F1 score of top 10 predicted phrases (F1@10).