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Computational models of referring : a study in cognitive science / Kees van Deemter.

By: Deemter, Kees van [author.].
Material type: TextTextSeries: JSTOR eBooks.Publisher: Cambridge, Massachusetts : The MIT Press, [2016]Copyright date: ©2016Description: 1 online resource (x, 339 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9780262335324; 0262335328.Subject(s): Reference (Linguistics) | Presupposition (Logic) | Computational linguisticsGenre/Form: Electronic books.Additional physical formats: Print version:: Computational models of referring.DDC classification: 410.1/835 LOC classification: P325.5.R44 | D43 2015Online resources: Click here to view this ebook.
Contents:
First part : Setting the stage -- Aims and scope of this book -- Theories of reference -- They psychology of reference production -- Second part : solving the classic REG problem -- Getting computers to refer -- Testing REG algorithms : the TUNA experiment -- Probabilistic and other alternatives to teh classic REG algorithms -- Third part : Generating a wider class of RES -- First extension : using proper names -- Second extension : referring to sets -- Third extension : using gradable properties -- Fourth extension : exploiting modern knowledge representation -- The question of referability -- Fourth part : generalizing reference generation -- First challenge : large domains -- Second challenege : breakdown of common knowledge -- Third challenge : approximate reference -- Fourth challenge : going beyond indentification -- Epilogue.
Summary: "To communicate, speakers need to make it clear what they are talking about. The act of referring, which anchors words to things, is a fundamental aspect of language. In this book, Kees van Deemter shows that computational models of reference offer attractive tools for capturing the complexity of referring. Indeed, the models van Deemter presents cover many issues beyond the basic idea of referring to an object, including reference to sets, approximate descriptions, descriptions produced under uncertainty concerning the hearer's knowledge, and descriptions that aim to inform or influence the hearer. The book, which can be read as a case study in cognitive science, draws on perspectives from across the cognitive sciences, including philosophy, experimental psychology, formal logic, and computer science. Van Deemter advocates a combination of computational modeling and careful experimentation as the preferred method for expanding these insights. He then shows this method in action, covering a range of algorithms and a variety of methods for testing them. He shows that the method allows us to model logically complicated referring expressions, and demonstrates how we can gain an understanding of reference in situations where the speaker's knowledge is difficult to assess or where the referent resists exact definition. Finally, he proposes a program of research that addresses the open questions that remain in this area, arguing that this program can significantly enhance our understanding of human communication"--MIT CogNet.
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Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
Online
P325.5.R44 D43 2015 (Browse shelf) https://ezproxy.uttyler.edu/login?url=http://www.jstor.org/stable/10.2307/j.ctt1c2cqmn Available ocn949885446

Includes bibliographical references and index.

First part : Setting the stage -- Aims and scope of this book -- Theories of reference -- They psychology of reference production -- Second part : solving the classic REG problem -- Getting computers to refer -- Testing REG algorithms : the TUNA experiment -- Probabilistic and other alternatives to teh classic REG algorithms -- Third part : Generating a wider class of RES -- First extension : using proper names -- Second extension : referring to sets -- Third extension : using gradable properties -- Fourth extension : exploiting modern knowledge representation -- The question of referability -- Fourth part : generalizing reference generation -- First challenge : large domains -- Second challenege : breakdown of common knowledge -- Third challenge : approximate reference -- Fourth challenge : going beyond indentification -- Epilogue.

"To communicate, speakers need to make it clear what they are talking about. The act of referring, which anchors words to things, is a fundamental aspect of language. In this book, Kees van Deemter shows that computational models of reference offer attractive tools for capturing the complexity of referring. Indeed, the models van Deemter presents cover many issues beyond the basic idea of referring to an object, including reference to sets, approximate descriptions, descriptions produced under uncertainty concerning the hearer's knowledge, and descriptions that aim to inform or influence the hearer. The book, which can be read as a case study in cognitive science, draws on perspectives from across the cognitive sciences, including philosophy, experimental psychology, formal logic, and computer science. Van Deemter advocates a combination of computational modeling and careful experimentation as the preferred method for expanding these insights. He then shows this method in action, covering a range of algorithms and a variety of methods for testing them. He shows that the method allows us to model logically complicated referring expressions, and demonstrates how we can gain an understanding of reference in situations where the speaker's knowledge is difficult to assess or where the referent resists exact definition. Finally, he proposes a program of research that addresses the open questions that remain in this area, arguing that this program can significantly enhance our understanding of human communication"--MIT CogNet.

Description based on print version record.

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