Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of The 13th International Conference on Natural Language Generation |
| Editors | Brian Davis, Yvette Graham, John Kelleher, Yaji Sripada |
| Pages | 237-241 |
| Number of pages | 5 |
| Publication status | Published - Dec 2020 |
| Externally published | Yes |
| Event | 13th International Conference on Natural Language Generation, INLG 2020 - Virtual, Dublin, Ireland Duration: 15 Dec 2020 → 18 Dec 2020 |
Abstract
We propose a shared task on abstractive snippet generation for web pages, a novel task of generating query-biased abstractive summaries for documents that are to be shown on a search results page. Conventional snippets are extractive in nature, which recently gave rise to copyright claims from news publishers as well as a new copyright legislation being passed in the European Union, limiting the fair use of web page contents for snippets. At the same time, abstractive summarization has matured considerably in recent years, potentially allowing for more personalization of snippets in the future. Taken together, these facts render further research into generating abstractive snippets both timely and promising.
ASJC Scopus subject areas
- Arts and Humanities(all)
- Language and Linguistics
- Computer Science(all)
- Software
- Social Sciences(all)
- Linguistics and Language
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
Proceedings of The 13th International Conference on Natural Language Generation. ed. / Brian Davis; Yvette Graham; John Kelleher; Yaji Sripada. 2020. p. 237-241.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Task Proposal
T2 - 13th International Conference on Natural Language Generation, INLG 2020
AU - Syed, Shahbaz
AU - Chen, Wei Fan
AU - Hagen, Matthias
AU - Stein, Benno
AU - Wachsmuth, Henning
AU - Potthast, Martin
PY - 2020/12
Y1 - 2020/12
N2 - We propose a shared task on abstractive snippet generation for web pages, a novel task of generating query-biased abstractive summaries for documents that are to be shown on a search results page. Conventional snippets are extractive in nature, which recently gave rise to copyright claims from news publishers as well as a new copyright legislation being passed in the European Union, limiting the fair use of web page contents for snippets. At the same time, abstractive summarization has matured considerably in recent years, potentially allowing for more personalization of snippets in the future. Taken together, these facts render further research into generating abstractive snippets both timely and promising.
AB - We propose a shared task on abstractive snippet generation for web pages, a novel task of generating query-biased abstractive summaries for documents that are to be shown on a search results page. Conventional snippets are extractive in nature, which recently gave rise to copyright claims from news publishers as well as a new copyright legislation being passed in the European Union, limiting the fair use of web page contents for snippets. At the same time, abstractive summarization has matured considerably in recent years, potentially allowing for more personalization of snippets in the future. Taken together, these facts render further research into generating abstractive snippets both timely and promising.
UR - http://www.scopus.com/inward/record.url?scp=85123297522&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85123297522
SN - 9781952148545
SP - 237
EP - 241
BT - Proceedings of The 13th International Conference on Natural Language Generation
A2 - Davis, Brian
A2 - Graham, Yvette
A2 - Kelleher, John
A2 - Sripada, Yaji
Y2 - 15 December 2020 through 18 December 2020
ER -