Interactive Abstractive Summarization for Event News Tweets

Ori Shapira, Hadar Ronen, Meni Adler, Yael Amsterdamer, Judit Bar-Ilan, Ido Dagan


Abstract
We present a novel interactive summarization system that is based on abstractive summarization, derived from a recent consolidated knowledge representation for multiple texts. We incorporate a couple of interaction mechanisms, providing a bullet-style summary while allowing to attain the most important information first and interactively drill down to more specific details. A usability study of our implementation, for event news tweets, suggests the utility of our approach for text exploration.
Anthology ID:
D17-2019
Volume:
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
109–114
Language:
URL:
https://aclanthology.org/D17-2019
DOI:
10.18653/v1/D17-2019
Bibkey:
Cite (ACL):
Ori Shapira, Hadar Ronen, Meni Adler, Yael Amsterdamer, Judit Bar-Ilan, and Ido Dagan. 2017. Interactive Abstractive Summarization for Event News Tweets. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 109–114, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Interactive Abstractive Summarization for Event News Tweets (Shapira et al., EMNLP 2017)
Copy Citation:
PDF:
https://aclanthology.org/D17-2019.pdf