| 書目名稱 | From Extractive to Abstractive Summarization: A Journey |
| 編輯 | Parth Mehta,Prasenjit Majumder |
| 視頻video | http://file.papertrans.cn/349/348674/348674.mp4 |
| 概述 | Provides an overview of the transition from extractive to abstractive summarization and how they can be combined to create a practical summarization system.Covers in detail ways to build ensembles fro |
| 圖書封面 |  |
| 描述 | This book describes recent advances in text summarization, identifies remaining gaps and challenges, and proposes ways to overcome them. It begins with one of the most frequently discussed topics in text summarization –? ‘sentence extraction’ –, examines the effectiveness of current techniques in domain-specific text summarization, and proposes several improvements.?.In turn, the book describes the application of summarization in the legal and scientific domains, describing two new corpora that consist of more than 100 thousand court judgments and more than 20 thousand scientific articles, with the corresponding manually written summaries. The availability of these large-scale corpora opens up the possibility of using the now popular data-driven approaches based on deep learning. The book then highlights the effectiveness of neural sentence extraction approaches, which perform just as well as rule-based approaches, but without the need for any manual annotation. As a next step, multiple techniques for creating ensembles of sentence extractors – which deliver better and more robust summaries – are proposed. In closing, the book presents a neural network-based model for sentence comp |
| 出版日期 | Book 2019 |
| 關鍵詞 | Automatic Text Summarization; Legal document summarization; Scientific document summarization; Ensemble |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-13-8934-4 |
| isbn_softcover | 978-981-13-8936-8 |
| isbn_ebook | 978-981-13-8934-4 |
| copyright | Springer Nature Singapore Pte Ltd. 2019 |
|Archiver|手機版|小黑屋|
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