Automatic Text Summarization: A State-of-the-Art Review

被引：6

作者：

Klymenko, Oleksandra ^{[1
]}

Braun, Daniel ^{[1
]}

Matthes, Florian ^{[1
]}

机构：

[1] Tech Univ Munich, Dept Informat, Munich, Germany

来源：

PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS (ICEIS), VOL 1 | 2020年

关键词：

Text Summarization; Natural Language Generation; Summary Evaluation;

D O I：

10.5220/0009723306480655

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Despite the progress that has been achieved in over 50 years of research, automatic text summarization systems are still far from perfect, posing many challenges to the researchers in the field. This paper provides an overview of the most prominent algorithms for automatic text summarization that were proposed in the last years, as well as describes automatic and manual evaluation methods that are currently widely adopted.

引用

页码：648 / 655

页数：8

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