A Survey of the State-of-the-Art Models in Neural Abstractive Text Summarization

A Survey of the State-of-the-Art Models in Neural Abstractive Text Summarization

Dealing with vast amounts of textual data requires the use of efficient systems. Automatic summarization systems are capable of addressing this issue. Therefore, it becomes highly essential to work on the design of existing automatic summarization systems and innovate them to make them capable of me...

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Bibliographic Details
Main Authors: Ayesha Ayub Syed, Ford Lumban Gaol, Tokuro Matsuo
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Abstractive text summarization
encoder
decoder
training
optimization
evaluation
Online Access:https://ieeexplore.ieee.org/document/9328413/

Internet

https://ieeexplore.ieee.org/document/9328413/

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