Automatic Summarization

被引:227
|
作者
Nenkova, Ani [1 ]
McKeown, Kathleen [2 ]
机构
[1] Univ Penn, Philadelphia, PA 19104 USA
[2] Columbia Univ, New York, NY USA
来源
基金
美国国家科学基金会;
关键词
D O I
10.1561/1500000015
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It has now been 50 years since the publication of Luhn's seminal paper on automatic summarization. During these years the practical need for automatic summarization has become increasingly urgent and numerous papers have been published on the topic. As a result, it has become harder to find a single reference that gives an overview of past efforts or a complete view of summarization tasks and necessary system components. This article attempts to fill this void by providing a comprehensive overview of research in summarization, including the more traditional efforts in sentence extraction as well as the most novel recent approaches for determining important content, for domain and genre specific summarization and for evaluation of summarization. We also discuss the challenges that remain open, in particular the need for language generation and deeper semantic understanding of language that would be necessary for future advances in the field.
引用
收藏
页码:103 / 233
页数:131
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