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BOOK SERIES IN NATURAL LANGUAGE PROCESSING<br>
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John Benjamins’ NLP series (NLP-3)<br>
<a href="http://www.wlv.ac.uk/~le1825/JB/series.htm" eudora="autourl">http://www.wlv.ac.uk/~le1825/JB/series.htm</a><br>
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Book series editor Ruslan Mitkov<br>
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AUTOMATIC SUMMARIZATION<br>
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Inderjeet Mani<br>
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</font><font face="Courier, Courier" size=2> John Benjamins
Pub Co; ISBN: 1588110591 (hardcover), 1588110605 (paperback)<br>
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</font><font face="Courier, Courier" size=2>With the explosion in the
quantity of on-line text and multimedia <br>
information in recent years, there has been a renewed interest in <br>
automatic summarization. This book provides a systematic introduction to
<br>
the field, explaining basic definitions, the strategies used by human
<br>
summarizers, and automatic methods that leverage linguistic and <br>
statistical knowledge to produce extracts and abstracts. Drawing from a
<br>
wealth of research in artificial intelligence, natural language <br>
processing, and information retrieval, the book also includes detailed
<br>
assessments of evaluation methods and new topics such as multi-document
<br>
and multimedia summarization.<br>
<br>
Previous automatic summarization books have been either collections of
<br>
specialized papers, or else authored books with only a chapter or two
<br>
devoted to the field as a whole. This is the first textbook on the <br>
subject, based on teaching materials used in two one-semester <br>
courses. To further help the student reader, the book includes detailed
<br>
case studies, accompanied by end-of-chapter reviews and an extensive
<br>
glossary.<br>
<br>
The book is intended for students and researchers, as well as <br>
information technology managers, librarians, and anyone else interested
<br>
in the subject.<br>
<br>
TABLE OF CONTENTS<br>
<br>
PREFACE <br>
<br>
I. PRELIMINARIES<br>
1. Introduction <br>
2. Basic Notions for Summarization <br>
3. Abstract Architecture for Summarization <br>
4. Summarization Approaches <br>
5. Current Applications <br>
6. Conclusion <br>
7. Review <br>
<br>
II. PROFESSIONAL SUMMARIZING <br>
1. Introduction <br>
2. The stages of abstracting <br>
3. Abstracting Strategies <br>
4. Reading for Abstracting <br>
5. Revision <br>
6. Psychological Experiments <br>
7. Structure of Empirical Abstracts <br>
8. Conclusion <br>
9. Review <br>
<br>
III. EXTRACTION <br>
1. Introduction <br>
2. The Edmundsonian Paradigm <br>
3. Corpus Based Sentence Extraction <br>
3.1 General Considerations <br>
3.2 Aspects of Learning Approaches <br>
4. Coherence of Extracts <br>
5. Conclusion <br>
6. Review <br>
<br>
IV. REVISION <br>
1. Introduction <br>
2. Shallow Coherence Smoothing <br>
3. Full Revision to Improve Informativeness <br>
3.1 Case Study: Full Revision <br>
3.2 Related Work <br>
3.3 Implications <br>
4. Text Compaction <br>
5. Conclusion <br>
6. Review <br>
<br>
V. DISCOURSE-LEVEL INFORMATION <br>
1. Introduction <br>
2. Text Cohesion <br>
2.1 Introduction <br>
2.2 Cohesion Graph Topology <br>
2.3 Topic Characterization <br>
3. Text Coherence <br>
3.1 Introduction <br>
3.2 Coherence Relations <br>
3.3 Rhetorical Structure Theory (RST) <br>
3.4 Rhetorical Structure and Cue Phrases <br>
3.5 The Document Scheme, Revisited <br>
4. Conclusion <br>
5. Review <br>
<br>
VI. ABSTRACTION <br>
1. Introduction <br>
2. Abstraction from Templates <br>
2.1 Introduction <br>
2.2 Case Study: Sketchy Scripts <br>
2.3 Modern Information Extraction <br>
3. Abstraction by Term Rewriting <br>
4. Abstraction using Event Relations <br>
5. Abstraction using a Concept Hierarchy <br>
5.1. Domain Knowledge Base Activation <br>
5.2. Generic Thesaurus Activation <br>
6. Synthesis for Abstraction <br>
6.1. Pretty printing <br>
6.2. Graphical Output <br>
6.3. Extraction <br>
6.4. Generation for Synthesis <br>
7. Conclusion <br>
8. Review <br>
<br>
VII. MULTI-DOCUMENT SUMMARIZATION <br>
1. Introduction <br>
2. Types of relationships across documents <br>
3. MDS methods <br>
3.1 Overview <br>
3.2 Specific Approaches <br>
4. Case Study: Biographical Summarization <br>
4.1 Introduction <br>
4.2 Example Architecture <br>
4.3 Algorithm Steps <br>
4.4 Bio Summarizer Components <br>
4.5 Assessment <br>
5. Conclusion <br>
6. Review <br>
<br>
VIII. MULTIMEDIA SUMMARIZATION <br>
1. Introduction <br>
2. Dialog Summarization <br>
3. Summarization of Video <br>
4. Summarization of Diagrams <br>
5. Automatic Multimedia Briefing Generation <br>
6. Conclusion <br>
7. Review <br>
<br>
IX. EVALUATION <br>
1. Introduction <br>
2. Intrinsic Methods <br>
2.1 Assessing Agreement Between Subjects <br>
2.2 Quality <br>
2.3 Informativeness <br>
2.4 Component-level tests <br>
3. Extrinsic Methods <br>
3.1 Relevance Assessment <br>
3.2 Reading Comprehension <br>
3.3 Presentation Strategies <br>
3.4 Mature System Evaluation <br>
4. Conclusion <br>
5. Review <br>
<br>
X. POSTSCRIPT <br>
<br>
REFERENCES <br>
INDEX<br>
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