Abstractive Text Summarization Using LSTMs with Rich Features

Autor:	Huong Le Thanh, Viet Nguyen Quoc, Tuan Luu Minh
Rok vydání:	2020
Předmět:	business.industry Computer science Vietnamese language Artificial intelligence business computer.software_genre Automatic summarization computer language.human_language Natural language processing
Zdroj:	Communications in Computer and Information Science ISBN: 9789811561672 PACLING
Popis:	ive text summarization using sequence-to-sequence networks have been successful for short text. However, these models have shown their limitations in summarizing long text as they forget sentences in long distance. We propose an abstractive summarization model using rich features to overcome this weakness. The proposed system has been tested with two datasets: an English dataset (CNN/Daily Mail) and a Vietnamese dataset (Baomoi). Experimental results show that our model significantly outperforms recently proposed models on both datasets.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::602f41e602d7712e61555f33010730bc https://doi.org/10.1007/978-981-15-6168-9_3 Zobrazit plný text záznamu