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From extractive to abstractive summa...

Mehta, Parth.

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From extractive to abstractive summarization = a journey /

Record Type:	Electronic resources : Monograph/item
Title/Author:	From extractive to abstractive summarization/ by Parth Mehta, Prasenjit Majumder.
Reminder of title:	a journey /
Author:	Mehta, Parth.
other author:	Majumder, Prasenjit.
Published:	Singapore :Springer Singapore : : 2019.,
Description:	xi, 116 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computational linguistics. -
Online resource:	https://doi.org/10.1007/978-981-13-8934-4
ISBN:	9789811389344

From extractive to abstractive summarization = a journey /
Mehta, Parth.

From extractive to abstractive summarizationa journey /[electronic resource] :by Parth Mehta, Prasenjit Majumder. - Singapore :Springer Singapore :2019. - xi, 116 p. :ill., digital ;24 cm.

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 compression. Overall the book takes readers on a journey that begins with simple sentence extraction and ends in abstractive summarization, while also covering key topics like ensemble techniques and domain-specific summarization, which have not been explored in detail prior to this.

ISBN: 9789811389344

Standard No.: 10.1007/978-981-13-8934-4doiSubjects--Topical Terms:

606540
Computational linguistics.

LC Class. No.: P98 / .M44 2019

Dewey Class. No.: 410.285

From extractive to abstractive summarization = a journey /
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245 1 0 $a From extractive to abstractive summarization $h [electronic resource] : $b a journey / $c by Parth Mehta, Prasenjit Majumder.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a xi, 116 p. : $b ill., digital ; $c 24 cm.
520 $a 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 compression. Overall the book takes readers on a journey that begins with simple sentence extraction and ends in abstractive summarization, while also covering key topics like ensemble techniques and domain-specific summarization, which have not been explored in detail prior to this.
650 0 $a Computational linguistics. $3 606540
650 0 $a Automatic abstracting. $3 769779
650 1 4 $a Performance and Reliability. $3 893430
650 2 4 $a Computer Communication Networks. $3 775497
650 2 4 $a Information Systems Applications (incl. Internet) $3 1565452
700 1 $a Majumder, Prasenjit. $3 3300601
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773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-13-8934-4
950 $a Computer Science (SpringerNature-11645)