Computational models of referring :: a study in cognitive science /
"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...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Massachusetts :
The MIT Press,
[2016]
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | "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 |
| Beschreibung: | 1 online resource (x, 339 pages) |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9780262335324 0262335328 9780262335317 026233531X |
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| 245 | 1 | 0 | |a Computational models of referring : |b a study in cognitive science / |c Kees van Deemter. |
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| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | 0 | |t First part : Setting the stage -- |t Aims and scope of this book -- |t Theories of reference -- |t They psychology of reference production -- |t Second part : solving the classic REG problem -- |t Getting computers to refer -- |t Testing REG algorithms : the TUNA experiment -- |t Probabilistic and other alternatives to teh classic REG algorithms -- |t Third part : Generating a wider class of RES -- |t First extension : using proper names -- |t Second extension : referring to sets -- |t Third extension : using gradable properties -- |t Fourth extension : exploiting modern knowledge representation -- |t The question of referability -- |t Fourth part : generalizing reference generation -- |t First challenge : large domains -- |t Second challenege : breakdown of common knowledge -- |t Third challenge : approximate reference -- |t Fourth challenge : going beyond indentification -- |t Epilogue. |
| 520 | |a "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 | ||
| 588 | 0 | |a Print version record. | |
| 546 | |a English. | ||
| 650 | 0 | |a Reference (Linguistics) |0 http://id.loc.gov/authorities/subjects/sh85112184 | |
| 650 | 0 | |a Presupposition (Logic) |0 http://id.loc.gov/authorities/subjects/sh85106584 | |
| 650 | 0 | |a Computational linguistics. |0 http://id.loc.gov/authorities/subjects/sh85077224 | |
| 650 | 6 | |a Référence (Linguistique) | |
| 650 | 6 | |a Présupposition (Logique) | |
| 650 | 6 | |a Linguistique informatique. | |
| 650 | 7 | |a computational linguistics. |2 aat | |
| 650 | 7 | |a LANGUAGE ARTS & DISCIPLINES |x Linguistics |x Historical & Comparative. |2 bisacsh | |
| 650 | 7 | |a Computational linguistics |2 fast | |
| 650 | 7 | |a Presupposition (Logic) |2 fast | |
| 650 | 7 | |a Reference (Linguistics) |2 fast | |
| 653 | |a LINGUISTICS & LANGUAGE/General | ||
| 653 | |a COGNITIVE SCIENCES/General | ||
| 653 | |a COMPUTER SCIENCE/General | ||
| 758 | |i has work: |a Computational models of referring (Text) |1 https://id.oclc.org/worldcat/entity/E39PCG9jRDHFcv7Y76BfdYhk8P |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Deemter, Kees van. |t Computational models of referring. |d Cambridge, MA : The MIT Press, [2016] |z 9780262034555 |w (DLC) 2015038523 |w (OCoLC)927241516 |
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Datensatz im Suchindex
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| author | Deemter, Kees van |
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| author_facet | Deemter, Kees van |
| author_role | aut |
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| callnumber-first | P - Language and Literature |
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| 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. |
| ctrlnum | (OCoLC)949885446 |
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| dewey-hundreds | 400 - Language |
| dewey-ones | 410 - Linguistics |
| dewey-raw | 410.1/835 |
| dewey-search | 410.1/835 |
| dewey-sort | 3410.1 3835 |
| dewey-tens | 410 - Linguistics |
| discipline | Sprachwissenschaft |
| format | Electronic eBook |
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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. 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| id | ZDB-4-EBA-ocn949885446 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-27T13:27:12Z |
| institution | BVB |
| isbn | 9780262335324 0262335328 9780262335317 026233531X |
| language | English |
| oclc_num | 949885446 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (x, 339 pages) |
| psigel | ZDB-4-EBA |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | The MIT Press, |
| record_format | marc |
| spelling | Deemter, Kees van, author. http://id.loc.gov/authorities/names/n95110302 Computational models of referring : a study in cognitive science / Kees van Deemter. Cambridge, Massachusetts : The MIT Press, [2016] ©2016 1 online resource (x, 339 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier text file rdaft 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 Print version record. English. Reference (Linguistics) http://id.loc.gov/authorities/subjects/sh85112184 Presupposition (Logic) http://id.loc.gov/authorities/subjects/sh85106584 Computational linguistics. http://id.loc.gov/authorities/subjects/sh85077224 Référence (Linguistique) Présupposition (Logique) Linguistique informatique. computational linguistics. aat LANGUAGE ARTS & DISCIPLINES Linguistics Historical & Comparative. bisacsh Computational linguistics fast Presupposition (Logic) fast Reference (Linguistics) fast LINGUISTICS & LANGUAGE/General COGNITIVE SCIENCES/General COMPUTER SCIENCE/General has work: Computational models of referring (Text) https://id.oclc.org/worldcat/entity/E39PCG9jRDHFcv7Y76BfdYhk8P https://id.oclc.org/worldcat/ontology/hasWork Print version: Deemter, Kees van. Computational models of referring. Cambridge, MA : The MIT Press, [2016] 9780262034555 (DLC) 2015038523 (OCoLC)927241516 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1238004 Volltext |
| spellingShingle | Deemter, Kees van Computational models of referring : a study in cognitive science / 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. Reference (Linguistics) http://id.loc.gov/authorities/subjects/sh85112184 Presupposition (Logic) http://id.loc.gov/authorities/subjects/sh85106584 Computational linguistics. http://id.loc.gov/authorities/subjects/sh85077224 Référence (Linguistique) Présupposition (Logique) Linguistique informatique. computational linguistics. aat LANGUAGE ARTS & DISCIPLINES Linguistics Historical & Comparative. bisacsh Computational linguistics fast Presupposition (Logic) fast Reference (Linguistics) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85112184 http://id.loc.gov/authorities/subjects/sh85106584 http://id.loc.gov/authorities/subjects/sh85077224 |
| title | Computational models of referring : a study in cognitive science / |
| title_alt | 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. |
| title_auth | Computational models of referring : a study in cognitive science / |
| title_exact_search | Computational models of referring : a study in cognitive science / |
| title_full | Computational models of referring : a study in cognitive science / Kees van Deemter. |
| title_fullStr | Computational models of referring : a study in cognitive science / Kees van Deemter. |
| title_full_unstemmed | Computational models of referring : a study in cognitive science / Kees van Deemter. |
| title_short | Computational models of referring : |
| title_sort | computational models of referring a study in cognitive science |
| title_sub | a study in cognitive science / |
| topic | Reference (Linguistics) http://id.loc.gov/authorities/subjects/sh85112184 Presupposition (Logic) http://id.loc.gov/authorities/subjects/sh85106584 Computational linguistics. http://id.loc.gov/authorities/subjects/sh85077224 Référence (Linguistique) Présupposition (Logique) Linguistique informatique. computational linguistics. aat LANGUAGE ARTS & DISCIPLINES Linguistics Historical & Comparative. bisacsh Computational linguistics fast Presupposition (Logic) fast Reference (Linguistics) fast |
| topic_facet | Reference (Linguistics) Presupposition (Logic) Computational linguistics. Référence (Linguistique) Présupposition (Logique) Linguistique informatique. computational linguistics. LANGUAGE ARTS & DISCIPLINES Linguistics Historical & Comparative. Computational linguistics |
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| work_keys_str_mv | AT deemterkeesvan computationalmodelsofreferringastudyincognitivescience |