Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization

Dongyub Lee, Myeong Cheol Shin, Taesun Whang, Seungwoo Cho, Byeongil Ko, Daniel Lee, EungGyun Kim, Jaechoon Jo


Abstract
Text summarization refers to the process that generates a shorter form of text from the source document preserving salient information. Many existing works for text summarization are generally evaluated by using recall-oriented understudy for gisting evaluation (ROUGE) scores. However, as ROUGE scores are computed based on n-gram overlap, they do not reflect semantic meaning correspondences between generated and reference summaries. Because Korean is an agglutinative language that combines various morphemes into a word that express several meanings, ROUGE is not suitable for Korean summarization. In this paper, we propose evaluation metrics that reflect semantic meanings of a reference summary and the original document, Reference and Document Aware Semantic Score (RDASS). We then propose a method for improving the correlation of the metrics with human judgment. Evaluation results show that the correlation with human judgment is significantly higher for our evaluation metrics than for ROUGE scores.
Anthology ID:
2020.coling-main.491
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
5604–5616
Language:
URL:
https://aclanthology.org/2020.coling-main.491
DOI:
10.18653/v1/2020.coling-main.491
Bibkey:
Cite (ACL):
Dongyub Lee, Myeong Cheol Shin, Taesun Whang, Seungwoo Cho, Byeongil Ko, Daniel Lee, EungGyun Kim, and Jaechoon Jo. 2020. Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization. In Proceedings of the 28th International Conference on Computational Linguistics, pages 5604–5616, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization (Lee et al., COLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.coling-main.491.pdf
Data
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