Extractive Summarization Based on Dynamic Memory Network
Keyword(s):
We present an extractive summarization model based on the Bert and dynamic memory network. The model based on Bert uses the transformer to extract text features and uses the pre-trained model to construct the sentence embeddings. The model based on Bert labels the sentences automatically without using any hand-crafted features and the datasets are symmetry labeled. We also present a dynamic memory network method for extractive summarization. Experiments are conducted on several summarization benchmark datasets. Our model shows comparable performance compared with other extractive summarization methods.
Keyword(s):
2012 ◽
Vol 39
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pp. 57-64
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2006 ◽
Vol 30
(14)
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pp. 1158-1174
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2018 ◽
Vol 19
(9)
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pp. 2817
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