Automatic Summarization

Overview

With the explosion in the quantity of on-line text and multimedia information in recent years, there has been a renewed interest in automatic summarization. This book provides a systematic introduction to the field, explaining basic definitions, the strategies used by human summarizers, and automatic methods that leverage linguistic and statistical knowledge to produce extracts and abstracts. Drawing from a wealth of research in artificial intelligence, natural language processing, and information retrieval, the ...
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Overview

With the explosion in the quantity of on-line text and multimedia information in recent years, there has been a renewed interest in automatic summarization. This book provides a systematic introduction to the field, explaining basic definitions, the strategies used by human summarizers, and automatic methods that leverage linguistic and statistical knowledge to produce extracts and abstracts. Drawing from a wealth of research in artificial intelligence, natural language processing, and information retrieval, the book also includes detailed assessments of evaluation methods and new topics such as multi-document and multimedia summarization. Previous automatic summarization books have been either collections of specialized papers, or else authored books with only a chapter or two devoted to the field as a whole. This is the first textbook on the subject, developed based on teaching materials used in two one-semester courses. To further help the student reader, the book includes detailed case studies, accompanied by end-of-chapter reviews and an extensive glossary.Audience: students and researchers, as well as information technology managers, librarians, and anyone else interested in the subject.
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Editorial Reviews

Shirley J. Linicum
Mani thoroughly analyzes a diverse body of research and demonstrates its relevance to automatic text summarization, and he presents this information in an extended, or organized format. As a first step toward providing a systematic introduction to this increasingly important and rapidly evolving field, this book represents a valuable contribution to the literature.
Hal Daumé III
For researchers in the field of machine translation, this book provides a sufficient introduction to summarization to enable them to begin work in cross-lingual summarization.
Chris Paice in Computational Linguistics
Since this is the only textbook in its field, it will probably become required reading for new researchers, who will assume that it provides a full and balanced view...the book certainly provides a timely and informative overview of automatic summarization, and all researchers with an interest in this important field will wish to have it on their bookshelf.
Michael McQuaid
[...] there are no other obvious candidates for comparison as a textbook on automatic document summarization.
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Product Details

Table of Contents

Preface
Ch. 1 Preliminaries 1
Basic notions for summarization 6
Abstract architecture for summarization 14
Summarization approaches 18
Current applications 19
Ch. 2 Professional summarizing 27
The stages of abstracting 29
Abstracting strategies 32
Reading for abstracting 35
Revision 37
Psychological experiments 39
Structure of empirical abstracts 40
Ch. 3 Extraction 45
The Edmundsonian paradigm 47
Corpus based sentence extraction 53
Coherence of extracts 70
Ch. 4 Revision 77
Shallow coherence smoothing 78
Full revision to improve informativeness 81
Text compaction 85
Ch. 5 Discourse-level information 91
Text cohesion 93
Text coherence 106
Ch. 6 Abstraction 129
Abstraction from templates 130
Abstraction by term rewriting 139
Abstraction using event relations 144
Abstraction using a concept hierarchy 148
Synthesis for abstraction 152
Ch. 7 Multi-document summarization 169
Types of relationships across documents 173
MDS methods 179
Case study: Biographical summarization 194
Ch. 8 Multimedia summarization 209
Dialog summarization 209
Summarization of video 211
Summarization of diagrams 214
Automatic multimedia briefing generation 215
Ch. 9 Evaluation 221
Intrinsic methods 224
Extrinsic methods 241
Ch. 10 Postscript 261
References 263
Index 279
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