Abstractive text summarization using LSTM-CNN based deep learning

By Shengli Song, Haitao Huang, Tongxiao Ruan. Multimedia tools and applications, 2018

318 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/dc317f43d2d539b94725fa65a3e89aaea8a7aec6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yang Fang
2. Weidong Xiao
3. Yuheng Wang
4. Yong Zhang
5. Dan Li

Citations in the corpus

• Abstract Text Summarization with a Convolutional Seq2seq Model (2019, methodology): “Reference [29] proposed a text summarization model based on a LSTM-CNN framework that can construct summaries by exploring semantic phrases.”