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Understanding Editorial Text: A Computer Model of Argument Comprehension

  • Book
  • © 1990

Overview

Authors:
  1. Sergio J. Alvarado

    1. University of California, Davis, USA

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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 107)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xxvii
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  2. The Nature of Argument Comprehension

    • Sergio J. Alvarado
    Pages 1-23

  3. Representing Politico-Economic Knowledge

    • Sergio J. Alvarado
    Pages 25-48

  4. Beliefs and Belief Relationships

    • Sergio J. Alvarado
    Pages 49-80

  5. Argument Units

    • Sergio J. Alvarado
    Pages 81-119

  6. Meta-Argument Units

    • Sergio J. Alvarado
    Pages 121-142

  7. Recognizing Argument Structures

    • Sergio J. Alvarado
    Pages 143-168

  8. Memory Search and Retrieval

    • Sergio J. Alvarado
    Pages 169-193

  9. Annotated Example of the OpEd System

    • Sergio J. Alvarado
    Pages 195-260

  10. Future Work and Conclusions

    • Sergio J. Alvarado
    Pages 261-274

  11. Back Matter

    Pages 275-296
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Keywords

About this book

by Michael G. Dyer Natural language processing (NLP) is an area of research within Artificial Intelligence (AI) concerned with the comprehension and generation of natural language text. Comprehension involves the dynamic construction of conceptual representations, linked by causal relationships and organized/indexed for subsequent retrieval. Once these conceptual representations have been created, comprehension can be tested by means of such tasks as paraphrasing, question answering, and summarization. Higher-level cognitive tasks are also modeled within the NLP paradigm and include: translation, acquisition of word meanings and concepts through reading, analysis of goals and plans in multi-agent environments (e. g. , coalition and counterplanning behavior by narrative characters), invention of novel stories, recognition of abstract themes (such as irony and hypocrisy), extraction of the moral or point of a story, and justification/refutation of beliefs through argumentation. The robustness of conceptually-based text comprehension systems is directly related to the nature and scope of the knowledge constructs applied during conceptual analysis of the text. Until recently, conceptually-based natural language systems were developed for, and applied to, the task of narrative comprehension (Dyer, 1983a; Schank and Abelson, 1977; Wilensky, 1983). These systems worked by recognizing the goals and plans of narrative characters, and. using this knowledge to build a conceptual representation of the narrative, xx UNDERSTANDING EDITORIAL TEXT including actions and intentions which must be inferred to complete the representation. A large portion of text appearing in newspapers and magazines, however, is editorial in nature.

Authors and Affiliations

  • University of California, Davis, USA

    Sergio J. Alvarado

Bibliographic Information

  • Book Title: Understanding Editorial Text: A Computer Model of Argument Comprehension

  • Authors: Sergio J. Alvarado

  • Series Title: The Springer International Series in Engineering and Computer Science

  • DOI: https://doi.org/10.1007/978-1-4613-1561-2

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Kluwer Academic Publishers 1990

  • Hardcover ISBN: 978-0-7923-9123-4Published: 31 July 1990

  • Softcover ISBN: 978-1-4612-8836-7Published: 26 September 2011

  • eBook ISBN: 978-1-4613-1561-2Published: 06 December 2012

  • Series ISSN: 0893-3405

  • Edition Number: 1

  • Number of Pages: XXVIII, 296

  • Topics: Artificial Intelligence

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