Comprehensive Document Summarization with Refined Self-Matching Mechanism
Under the constraint of memory capacity of the neural network and the document length, it is difficult to generate summaries with adequate salient information. In this work, the self-matching mechanism is incorporated into the extractive summarization system at the encoder side, which allows the enc...
Main Authors: | Biqing Zeng, Ruyang Xu, Heng Yang, Zibang Gan, Wu Zhou |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-03-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/10/5/1864 |
Similar Items
-
Extractive Document Summarization Based on Dynamic Feature Space Mapping
by: Samira Ghodratnama, et al.
Published: (2020-01-01) -
Extractive multi-document text summarization based on graph independent sets
by: Taner Uçkan, et al.
Published: (2020-09-01) -
A review on automatic text summarization approaches
by: Basiron, H., et al.
Published: (2016) -
Extractive Multi-Document Summarization: A Review of Progress in the Last Decade
by: Zakia Jalil, et al.
Published: (2021-01-01) -
SFExt-PGAbs: Two-Stage Summarization Model for Long Document
by: ZHOU Weixiao, LAN Wenfei, XU Zhiming, ZHU Rongbo
Published: (2021-05-01)