This book highlights cutting-edge research relevant to the building of a computational model of reading comprehension, as in the processing and understanding of a natural language text or story. A distinguishing feature of the book is its emphasis on “real” understanding of “real” narrative texts rather than on syntactic parsing of single sentences taken out of context or on limited understanding of small, researcher-constructed stories.
The book takes an interdisciplinary approach to the study of reading, with contributions from computer science, psychology, and philosophy. Contributors cover the theoretical and psychological foundations of the research in discussions of what it means to understand a text, how one builds a computational model, and related issues in knowledge representation and reasoning. The book also addresses some of the broader issues that a natural language system must deal with, such as reading in context, linguistic novelty, and information extraction.
Dorrit Billman, Michael T. Cox, Eric Domeshek, Kurt Eiselt, Charles R. Fletcher, Richard Gerrig, Jennifer Holbrook, Eric Jones, Trent Lange, Mark Langston, Joe Magliano, Kavi Mahesh, Bonnie J. F. Meyer, Justin Peterson, William J. Rapaport, Ellen Riloff, Stuart C. Shapiro, Tom Trabasso, Charles M. Wharton.
Find the book:
Understanding Language Understanding: Computional Models of Reading
edited by Ashwin Ram, Kenneth MoormanMIT Press, Cambridge, MA, 1999, ISBN 978-0-262-18192-1
Preview the book: books.google.com/books?id=sL9Lsy3bDecC
Table of Contents
About the Editors
About the Authors
Chapter 1 (Introduction) Toward a Theory of Reading and Understanding, Ram, Moorman
Chapter 2 (Foundations) Cognition and Fiction, Rapaport, Shapiro
Chapter 3 (Sentence Processing) Sentence Processing in Understanding: Interaction and Integration of Knowledge Sources, Mahesh, Eiselt, Holbrook
Chapter 4 (Knowledge Representation) Capturing the Contents of Complex Narratives, Domeshek, Jones, Ram
Chapter 5 (Memory and Inference) Retrieval from Episodic Memory by Inferencing and Disambiguation, Lange, Wharton
Chapter 6 (Inference and Comprehension) A Connectionist Model of Narrative Comprehension, Langston, Trabasso, Magliano
Chapter 7 (Contextualization: Text Structure) Importance of Text Structure in Everyday Reading, Meyer
Chapter 8 (Contextualization: Goals) A Theory of Questions and Question Asking, Ram
Chapter 9 (Linguistic Novelty) Semantic Correspondence Theory, Peterson, Billman
Chapter 10 (Conceptual Novelty) Creativity in Reading: Understanding Novel Concepts, Moorman, Ram
Chapter 11 (Meta-Reasoning and Learning) On the Intersection of Story Understanding and Learning, Cox, Ram
Chapter 12 (Alternative Approaches) Information Extraction as a Stepping Stone toward Story Understanding, Riloff
Chapter 13 (Foundations Revisited) Text Processing and Narrative Worlds, Gerrig
Chapter 14 (Commentary) Computational Models of Reading and Understanding: What Good Are They?, Fletcher