Computational Models of Referring PDF Download

Author: Kees van Deemter
Publisher: MIT Press
ISBN: 0262034557
Category : Computers
Languages : en
Pages : 350

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8.6 Issues Raised by the Algorithms Proposed

Author: Ron Sun
Publisher: Cambridge University Press
ISBN: 0521674107
Category : Computers
Languages : en
Pages : 767

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A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.

Author: Michael Spivey
Publisher: Cambridge University Press
ISBN: 1139536141
Category : Psychology
Languages : en
Pages : 1297

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Our ability to speak, write, understand speech and read is critical to our ability to function in today's society. As such, psycholinguistics, or the study of how humans learn and use language, is a central topic in cognitive science. This comprehensive handbook is a collection of chapters written not by practitioners in the field, who can summarize the work going on around them, but by trailblazers from a wide array of subfields, who have been shaping the field of psycholinguistics over the last decade. Some topics discussed include how children learn language, how average adults understand and produce language, how language is represented in the brain, how brain-damaged individuals perform in terms of their language abilities and computer-based models of language and meaning. This is required reading for advanced researchers, graduate students and upper-level undergraduates who are interested in the recent developments and the future of psycholinguistics.

Author:
Publisher:
ISBN: 9781586924386
Category :
Languages : en
Pages :

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Author: Thad A. Polk
Publisher: MIT Press
ISBN: 9780262661164
Category : Psychology
Languages : en
Pages : 1300

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A comprehensive introduction to the computational modeling of human cognition.

Author: Kees van Deemter
Publisher: Frontiers Media SA
ISBN: 2889451607
Category : Communication
Languages : en
Pages : 245

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To communicate, speakers need to make it clear what they are talking about. Referring expressions play a crucial part in achieving this, by anchoring utterances to things. Examples of referring expressions include noun phrases such as “this phenomenon”, “it” and “the phenomenon to which this Topic is devoted”. Reference is studied throughout the Cognitive Sciences (from philosophy and logic to neuro-psychology, computer science and linguistics), because it is thought to lie at the core of all of communication. Recent years have seen a new wave of work on models of referring, as witnessed by a number of recent research projects, books, and journal Special Issues. The Research Topic “Models of Reference” in Frontiers in Psychology is a new milestone, focusing on contributions from Psycholinguistics and Computational Linguistics. The articles in it are concerned with such issues as audience design, overspecification, visual perception, and variation between speakers.

Author: Lise Fontaine
Publisher: Cambridge University Press
ISBN: 1107143470
Category : Language Arts & Disciplines
Languages : en
Pages : 255

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A comprehensive and integrated approach to referring expressions and their typical and atypical use in different language contexts.

Author: Jeanette Gundel
Publisher: Oxford University Press
ISBN: 0191510971
Category : Language Arts & Disciplines
Languages : en
Pages : 605

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Book Description
This handbook presents an overview of the phenomenon of reference - the ability to refer to and pick out entities - which is an essential part of human language and cognition. In the volume's 21 chapters, international experts in the field offer a critical account of all aspects of reference from a range of theoretical perspectives. Chapters in the first part of the book are concerned with basic questions related to different types of referring expression and their interpretation. They address questions about the role of the speaker - including speaker intentions - and of the addressee, as well as the role played by the semantics of the linguistic forms themselves in establishing reference. This part also explores the nature of such concepts as definite and indefinite reference and specificity, and the conditions under which reference may fail. The second part of the volume looks at implications and applications, with chapters covering such topics as the acquisition of reference by children, the processing of reference both in the human brain and by machines. The volume will be of interest to linguists in a wide range of subfields, including semantics, pragmatics, computational linguistics, and psycho- and neurolinguistics, as well as scholars in related fields such as philosophy and computer science.

Author: Marieka Brouwer Burg
Publisher: Springer
ISBN: 3319278339
Category : Social Science
Languages : en
Pages : 189

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This volume deals with the pressing issue of uncertainty in archaeological modeling. Detecting where and when uncertainty is introduced to the modeling process is critical, as are strategies for minimizing, reconciling, or accommodating such uncertainty. Included chapters provide unique perspectives on uncertainty in archaeological modeling, ranging in both theoretical and methodological orientation. The strengths and weaknesses of various identification and mitigation techniques are discussed, in particular sensitivity analysis. The chapters demonstrate that for archaeological modeling purposes, there is no quick fix for uncertainty; indeed, each archaeological model requires intensive consideration of uncertainty and specific applications for calibration and validation. As very few such techniques have been problematized in a systematic manner or published in the archaeological literature, this volume aims to provide guidance and direction to other modelers in the field by distilling some basic principles for model testing derived from insight gathered in the case studies presented. Additionally, model applications and their attendant uncertainties are presented from distinct spatio-temporal contexts and will appeal to a broad range of archaeological modelers. This volume will also be of interest to non-modeling archaeologists, as consideration of uncertainty when interpreting the archaeological record is also a vital concern for the development of non-formal (or implicit) models of human behavior in the past.

Author: Fahime Same
Publisher: Language Science Press
ISBN: 3961104719
Category : Language Arts & Disciplines
Languages : en
Pages : 276

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Book Description
Reference production, often termed Referring Expression Generation (REG) in computational linguistics, encompasses two distinct tasks: (1) one-shot REG, and (2) REG-in-context. One-shot REG explores which properties of a referent offer a unique description of it. In contrast, REG-in-context asks which (anaphoric) referring expressions are optimal at various points in discourse. This book offers a series of in-depth studies of the REG-in-context task. It thoroughly explores various aspects of the task such as corpus selection, computational methods, feature analysis, and evaluation techniques. The comparative study of different corpora highlights the pivotal role of corpus choice in REG-in-context research, emphasizing its influence on all subsequent model development steps. An experimental analysis of various feature-based machine learning models reveals that those with a concise set of linguistically-informed features can rival models with more features. Furthermore, this work highlights the importance of paragraph-related concepts, an area underexplored in Natural Language Generation (NLG). The book offers a thorough evaluation of different approaches to the REG-in-context task (rule-based, feature-based, and neural end-to-end), and demonstrates that well-crafted, non-neural models are capable of matching or surpassing the performance of neural REG-in-context models. In addition, the book delves into post-hoc experiments, aimed at improving the explainability of both neural and classical REG-in-context models. It also addresses other critical topics, such as the limitations of accuracy-based evaluation metrics and the essential role of human evaluation in NLG research. These studies collectively advance our understanding of REG-in-context. They highlight the importance of selecting appropriate corpora and targeted features. They show the need for context-aware modeling and the value of a comprehensive approach to model evaluation and interpretation. This detailed analysis of REG-in-context paves the way for developing more sophisticated, linguistically-informed, and contextually appropriate NLG systems.