Task Proposal: Abstractive Snippet Generation for Web Pages

Shahbaz Syed, Wei-Fan Chen, Matthias Hagen, Benno Stein, Henning Wachsmuth, Martin Potthast


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.
Anthology ID:
2020.inlg-1.30
Volume:
Proceedings of the 13th International Conference on Natural Language Generation
Month:
December
Year:
2020
Address:
Dublin, Ireland
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
237–241
Language:
URL:
https://www.aclweb.org/anthology/2020.inlg-1.30
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.inlg-1.30.pdf