Abstractive Summarization: A Survey of the State of the Art
2019 ◽
Vol 33
◽
pp. 9815-9822
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Keyword(s):
The focus of automatic text summarization research has exhibited a gradual shift from extractive methods to abstractive methods in recent years, owing in part to advances in neural methods. Originally developed for machine translation, neural methods provide a viable framework for obtaining an abstract representation of the meaning of an input text and generating informative, fluent, and human-like summaries. This paper surveys existing approaches to abstractive summarization, focusing on the recently developed neural approaches.
Keyword(s):
2021 ◽
Vol 10
(2)
◽
pp. 42-60
2019 ◽
Vol 8
(5S3)
◽
pp. 447-451
Keyword(s):
2020 ◽
Vol 1
(1)
◽
pp. 1
2020 ◽
Vol 34
(01)
◽
pp. 11-18
2021 ◽
Vol 10
(6)
◽
pp. 3148-3153