An Editorial Network for Enhanced Document Summarization

Edward Moroshko, Guy Feigenblat, Haggai Roitman, David Konopnicki


Abstract
We suggest a new idea of Editorial Network – a mixed extractive-abstractive summarization approach, which is applied as a post-processing step over a given sequence of extracted sentences. We further suggest an effective way for training the “editor” based on a novel soft-labeling approach. Using the CNN/DailyMail dataset we demonstrate the effectiveness of our approach compared to state-of-the-art extractive-only or abstractive-only baselines.
Anthology ID:
D19-5407
Volume:
Proceedings of the 2nd Workshop on New Frontiers in Summarization
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
57–63
Language:
URL:
https://aclanthology.org/D19-5407
DOI:
10.18653/v1/D19-5407
Bibkey:
Cite (ACL):
Edward Moroshko, Guy Feigenblat, Haggai Roitman, and David Konopnicki. 2019. An Editorial Network for Enhanced Document Summarization. In Proceedings of the 2nd Workshop on New Frontiers in Summarization, pages 57–63, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
An Editorial Network for Enhanced Document Summarization (Moroshko et al., EMNLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/D19-5407.pdf
Data
CNN/Daily Mail