Keyphrase Generation for Scientific Articles Using GANs (Student Abstract)

Avinash Swaminathan, Raj Kuwar Gupta, Haimin Zhang, Debanjan Mahata, Rakesh Gosangi, Rajiv Ratn Shah

AAAI 2020 pp. 13931-13932

doi:10.1609/AAAI.V34I10.7238 /aaai/2020/swaminathan2020aaai-keyphrase/

Abstract

In this paper, we present a keyphrase generation approach using conditional Generative Adversarial Networks (GAN). In our GAN model, the generator outputs a sequence of keyphrases based on the title and abstract of a scientific article. The discriminator learns to distinguish between machine-generated and human-curated keyphrases. We evaluate this approach on standard benchmark datasets. Our model achieves state-of-the-art performance in generation of abstractive keyphrases and is also comparable to the best performing extractive techniques. We also demonstrate that our method generates more diverse keyphrases and make our implementation publicly available1.

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Cite

Text

Swaminathan et al. "Keyphrase Generation for Scientific Articles Using GANs (Student Abstract)." AAAI Conference on Artificial Intelligence, 2020. doi:10.1609/AAAI.V34I10.7238

Markdown

[Swaminathan et al. "Keyphrase Generation for Scientific Articles Using GANs (Student Abstract)." AAAI Conference on Artificial Intelligence, 2020.](https://mlanthology.org/aaai/2020/swaminathan2020aaai-keyphrase/) doi:10.1609/AAAI.V34I10.7238

BibTeX

@inproceedings{swaminathan2020aaai-keyphrase,
  title     = {{Keyphrase Generation for Scientific Articles Using GANs (Student Abstract)}},
  author    = {Swaminathan, Avinash and Gupta, Raj Kuwar and Zhang, Haimin and Mahata, Debanjan and Gosangi, Rakesh and Shah, Rajiv Ratn},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2020},
  pages     = {13931-13932},
  doi       = {10.1609/AAAI.V34I10.7238},
  url       = {https://mlanthology.org/aaai/2020/swaminathan2020aaai-keyphrase/}
}