A Pointer Generator Network Model to Automatic Text Summarization and Headline Generation

In a world where information is growing rapidly every single day, we need tools to generate summary and headlines from text which is accurate as well as short and precise. In this paper, we have described a method for generating headlines from article. This is done by using hybrid pointer-generator...

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Veröffentlicht in:International journal of engineering and advanced technology Jg. 8; H. 5s3; S. 447 - 451
Hauptverfasser: Agrawal, Anubha, Saraswat, Sakshi, Javed, Hira
Format: Journal Article
Sprache:Englisch
Veröffentlicht: 14.09.2019
ISSN:2249-8958, 2249-8958
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Zusammenfassung:In a world where information is growing rapidly every single day, we need tools to generate summary and headlines from text which is accurate as well as short and precise. In this paper, we have described a method for generating headlines from article. This is done by using hybrid pointer-generator network with attention distribution and coverage mechanism on article which generates abstractive summarization followed by the application of encoder-decoder recurrent neural network with LSTM unit to generate headlines from the summary. Hybrid pointer generator model helps in removing inaccuracy as well as repetitions. We have used CNN / Daily Mail as our dataset.
ISSN:2249-8958
2249-8958
DOI:10.35940/ijeat.E1094.0785S319