Abstract

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.

Keywords

Automatic summarizationComputer scienceGlossarySubject (documents)Leverage (statistics)Field (mathematics)World Wide WebInformation retrievalArtificial intelligenceData scienceLinguistics

Affiliated Institutions

Related Publications

Workflow Management

This book offers a comprehensive introduction to workflow management, the management of business processes with information technology. By defining, analyzing, and redesigning a...

2002 The MIT Press eBooks 723 citations

Publication Info

Year
2001
Type
book
Citations
834
Access
Closed

External Links

Social Impact

Altmetric
PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

834
OpenAlex

Cite This

Inderjeet Mani (2001). Automatic Summarization. Natural language processing . https://doi.org/10.1075/nlp.3

Identifiers

DOI
10.1075/nlp.3