Cover
Contents
Historical Overview and Acknowledgements
1.1 Text Understanding and Information Management
1.2 Discourse Structure and Scientific Argument
1.3 Outline of this Book
Chapter 2: Information Retrieval and Citation Indexes
2.1 Information Needs in Science
2.2 Keyword-Based Search
2.2.1 Information Retrieval Methods
2.2.2 Evaluation of Information Retrieval Systems
2.3.1 The Citation System and Bibliometry
2.3.2 Citation Indexes and Search
3.1 Human Summarisation
3.1.1 Summary Journals and Professional Abstractors
3.1.2 Structure in Abstracts
3.2 Automatic Summarisation
3.2.1 Fact Extraction Methods
3.2.2 Text Extraction Methods
4.1 Rhetorical Extracts
4.2 Citation Maps
Chapter 5: Experimental Corpora
5.1 Computational Linguistics (CmpLG)
5.1.1 Source
5.1.2 Properties
5.1.3 Citation Behaviour
5.2 Chemistry
5.3 Genetics, Cardiology, Agriculture
5.4 SciXML
5.4.1 Description
5.4.2 Transformation from Source Formats
Chapter 6: The Knowledge Claim Discourse Model (KCDM)
6.1 Overview of the Model
6.2 Level 0: Goals in Argumentation
6.3 Level 1: Rhetorical Moves
6.4 Level 2: Knowledge Claim Attribution
6.5 Level 3: Hinging
6.6 Level 4: Linearisation and Presentation
6.7 Traditional Intension-Based Discourse Models
Chapter 7: Annotation Scheme Design
7.1 Fundamental Concepts
7.2 The KCA Scheme (Knowledge Claim Attribution)
7.3 The CFC Scheme (Citation Function Classification)
7.4 The AZ Scheme (Argumentative Zoning)
7.5 Alternative Scheme Definitions
Chapter 8: Reliability Studies
8.1 Agreement Metrics, Ceilings and Baselines
8.2 Study I: Knowledge Claim Attribution (KCA)
8.3 Study II: Argumentative Zoning (AZ)
8.4 Study III: Argumentative Zoning, Untrained
8.5 Study IV: Citation Function Classification (CFC)
8.6 Post-Hoc Analysis of Study II Data
Chapter 9: Discourse
9.1 Actions/States
9.2 Agents/Entities
9.3 Significance for Text Understanding
9.4.1 Formulaic Meta-Discourse
9.4.2 Ambiguous Mentions of Entities
9.4.3 Lexical Equivalence
9.5 Use of Meta-Discourse in the Literature
9.6 Cross-Discipline Differences in Meta-Discourse
Chapter 10: Features
10.1 Entity-Based Meta-Discourse (Ent)
10.2 Action-Based Meta-Discourse
10.3 Formulaic Meta-Discourse (Formu, F-Strength, Formu-XXX)
10.4 Scientific Attribution (SciAtt-X)
10.5 Citations (Cit)
10.6 Tense, Voice and Aspect
10.8 Structural Indicators (Loc, Struct)
10.9 Content and Sentence Length (Cont, Len)
Chapter 11: Automatic AZ, KCA and CFC
11.1 Feature Determination
11.2 Statistical Classification
Chapter 12: Evaluation
12.1 Intrinsic Evaluation
12.1.1 Automatic AZ
12.1.2 Automatic KCA
12.1.3 Automatic CFC
12.2 Extrinsic Evaluation (AZ)
12.2.1 Experimental Design
12.2.2 Results
Chapter 13: Applying the KCDM to Other Disciplines
13.1 Application to Chemistry
13.1.1 Domain-Knowledge-Free Annotation
13.1.2 Argumentative Zoning II
13.2.1 For Computer Science (Feltrim et al.)
13.2.2 For Biology (Mizuta and Collier)
13.2.3 For Astrophysics (Merity et al.)
13.2.4 For Legal Texts (Hachey and Grover)
13.3 Automatic Meta-Discourse Discovery
Chapter 14: Outlook
14.1 Support Tools for Scientific Writing
14.2 Automatic Review Generation
14.3 Scientific Summaries Beyond Extraction
14.4 Digital Libraries and Robust AZ
Chapter 15: Conclusions
15.1 An Interdisciplinary Project
15.2 Limitations
Appendix A: CmpLG-D Articles
Appendix B: DTD for SciXML
C.1 KCA Guidelines
C.2 AZ Guidelines (1998)
C.3 CFC Guidelines; Excerpt (2005)
D.1 Concept Lexicon
D.2 Formulaic Patterns
D.3 Entity Patterns
D.4 Action Lexicon
References
Author Index
Subject Index
Back Cover