Argument Mining: Linguistic Foundations
- 3h 31m
- Mathilde Janier, Patrick Saint-Dizier
- John Wiley & Sons (US)
- 2019
This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology. While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse. Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner.
About the Author
Mathilde Janier has co-authored over 15 publications, principally dealing with the annotation and modeling of argumentative dynamics in debate and dispute mediation. Her work mainly focuses on argumentation in dialogical contexts. Patrick Saint-Dizier is Senior Researcher at CNRS – IRIT Toulouse, France. His work is based on logic, language, argumentation, natural language processing and logic programming. He is the author and co-author of 11 books on these topics.
In this Book
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Introduction and Challenges
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The Structure of Argumentation
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The Linguistics of Argumentation
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Advanced Features of Argumentation for Argument Mining
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From Argumentation to Argument Mining
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Annotation Frameworks and Principles of Argument Analysis
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Argument Mining Applications and Systems
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A Computational Model and a Simple Grammar-Based Implementation
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Non-Verbal Dimensions of Argumentation—A Challenge for Argument Mining
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Bibliography
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