From Extractive to Abstractive Summarization: A Journey
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’ –, exam
- PDF / 2,331,585 Bytes
- 120 Pages / 453.544 x 683.151 pts Page_size
- 43 Downloads / 233 Views
om Extractive to Abstractive Summarization: A Journey
From Extractive to Abstractive Summarization: A Journey
Parth Mehta Prasenjit Majumder •
From Extractive to Abstractive Summarization: A Journey
123
Parth Mehta Information Retrieval and Language Processing Lab Dhirubhai Ambani Institute of Information and Communication Technology Gandhinagar, Gujarat, India
Prasenjit Majumder Information Retrieval and Language Processing Lab Dhirubhai Ambani Institute of Information and Communication Technology Gandhinagar, Gujarat, India
ISBN 978-981-13-8933-7 ISBN 978-981-13-8934-4 https://doi.org/10.1007/978-981-13-8934-4
(eBook)
© Springer Nature Singapore Pte Ltd. 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Preface
Research in the field of text summarisation has primarily been dominated by investigations of various sentence extraction techniques with a significant focus towards news articles. In this book, we intend to look beyond generic sentence extraction and instead focus on domain-specific summarisation, methods for creating ensembles of multiple extractive summarisation techniques and using sentence compression as the first step towards abstractive summarisation. We begin by proposing two new corpora, related to legal and scientific articles, for domain-specific summarisation. The first corpus is a collection of judgements delivered by the Supreme Court of India, with corresponding handwritten summaries written by legal experts. The second dataset is a collection of scientific articles related to the domain of computational linguistics and indexed in the ACL anthology. These two tasks highlight the challenges in domain-specific summarisation. The legal sum
Data Loading...
