From task to evaluation: an automatic text summarization review

Automatic summarization is attracting increasing attention as one of the most promising research areas. This technology has been tried in various real-world applications in recent years and achieved a good response. However, the applicability of conventional evaluation metrics cannot keep up with ra...

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Bibliographic Details
Published in:The Artificial intelligence review 2023-11, Vol.56 (Suppl 2), p.2477-2507
Main Authors: Lu, Lingfeng, Liu, Yang, Xu, Weiqiang, Li, Huakang, Sun, Guozi
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computer Science
Datasets
Language
Methods
Natural language
Semantics
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Summary:Automatic summarization is attracting increasing attention as one of the most promising research areas. This technology has been tried in various real-world applications in recent years and achieved a good response. However, the applicability of conventional evaluation metrics cannot keep up with rapidly evolving summarization task formats and ensuing indicator. After recent years of research, automatic summarization task requires not only readability and fluency, but also informativeness and consistency. Diversified application scenarios also bring new challenges both for generative language models and evaluation metrics. In this review, we analysis and specifically focus on the difference between the task format and the evaluation metrics.
ISSN:0269-2821
1573-7462
DOI:10.1007/s10462-023-10582-5