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Linguistic Structure Prediction

Noah A. Smith

Author : Noah A. Smith
Publisher : Morgan & Claypool Publishers
Page : 271 pages
File Size : 50,9 Mb
Release : 2011
Category : Computers
ISBN : 9781608454051

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Linguistic Structure Prediction by Noah A. Smith Pdf

A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. We also survey natural language processing problems to which these methods are being applied, and we address related topics in probabilistic inference, optimization, and experimental methodology. Table of Contents: Representations and Linguistic Data / Decoding: Making Predictions / Learning Structure from Annotated Data / Learning Structure from Incomplete Data / Beyond Decoding: Inference

Linguistic Structure Prediction

Noah A. Smith

Author : Noah A. Smith
Publisher : Springer Nature
Page : 248 pages
File Size : 53,8 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031021435

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Linguistic Structure Prediction by Noah A. Smith Pdf

A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. We also survey natural language processing problems to which these methods are being applied, and we address related topics in probabilistic inference, optimization, and experimental methodology. Table of Contents: Representations and Linguistic Data / Decoding: Making Predictions / Learning Structure from Annotated Data / Learning Structure from Incomplete Data / Beyond Decoding: Inference

Computational Modeling of Human Language Acquisition

Afra Alishahi,Bing Liu,Inderjeet Mani,Jörg Tiedemann,Manfred Stede,Noah A. Smith

Author : Afra Alishahi,Bing Liu,Inderjeet Mani,Jörg Tiedemann,Manfred Stede,Noah A. Smith
Publisher : Unknown
Page : 0 pages
File Size : 55,9 Mb
Release : 2011
Category : Artificial intelligence
ISBN : 8303102141

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Computational Modeling of Human Language Acquisition by Afra Alishahi,Bing Liu,Inderjeet Mani,Jörg Tiedemann,Manfred Stede,Noah A. Smith Pdf

A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. We also survey natural language processing problems to which these methods are being applied, and we address related topics in probabilistic inference, optimization, and experimental methodology. Table of Contents: Representations and Linguistic Data / Decoding: Making Predictions / Learning Structure from Annotated Data / Learning Structure from Incomplete Data / Beyond Decoding: Inference.

Advanced Structured Prediction

Sebastian Nowozin,Peter V. Gehler,Jeremy Jancsary,Christoph H. Lampert

Author : Sebastian Nowozin,Peter V. Gehler,Jeremy Jancsary,Christoph H. Lampert
Publisher : MIT Press
Page : 430 pages
File Size : 47,6 Mb
Release : 2014-12-05
Category : Computers
ISBN : 9780262028370

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Advanced Structured Prediction by Sebastian Nowozin,Peter V. Gehler,Jeremy Jancsary,Christoph H. Lampert Pdf

An overview of recent work in the field of structured prediction, the building of predictive machine learning models for interrelated and dependent outputs. The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components. These models are expressive and powerful, but exact computation is often intractable. A broad research effort in recent years has aimed at designing structured prediction models and approximate inference and learning procedures that are computationally efficient. This volume offers an overview of this recent research in order to make the work accessible to a broader research community. The chapters, by leading researchers in the field, cover a range of topics, including research trends, the linear programming relaxation approach, innovations in probabilistic modeling, recent theoretical progress, and resource-aware learning. Contributors Jonas Behr, Yutian Chen, Fernando De La Torre, Justin Domke, Peter V. Gehler, Andrew E. Gelfand, Sébastien Giguère, Amir Globerson, Fred A. Hamprecht, Minh Hoai, Tommi Jaakkola, Jeremy Jancsary, Joseph Keshet, Marius Kloft, Vladimir Kolmogorov, Christoph H. Lampert, François Laviolette, Xinghua Lou, Mario Marchand, André F. T. Martins, Ofer Meshi, Sebastian Nowozin, George Papandreou, Daniel Průša, Gunnar Rätsch, Amélie Rolland, Bogdan Savchynskyy, Stefan Schmidt, Thomas Schoenemann, Gabriele Schweikert, Ben Taskar, Sinisa Todorovic, Max Welling, David Weiss, Thomáš Werner, Alan Yuille, Stanislav Živný

Principles and Prediction

Mushira Eid,Gregory K. Iverson

Author : Mushira Eid,Gregory K. Iverson
Publisher : John Benjamins Publishing
Page : 403 pages
File Size : 45,6 Mb
Release : 1993-03-25
Category : Language Arts & Disciplines
ISBN : 9789027276971

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Principles and Prediction by Mushira Eid,Gregory K. Iverson Pdf

The volume is divided into four sections: typology, syntax, discourse and phonology. Two of the typology papers study the structure and organization of category systems (Joseph Greenberg, Linda Schwartz); the third discusses language typology and universals from the perspective of language acquisition (Fred Eckman). The eight papers in the syntax section are of three types. Edith Moravcsik and James Tai discuss 'general' issues of linguistic theory/domain. Four papers (Mushira Eid, Michael Kac, Nancy Hedberg, Larry Hutchinson) address specific analyses and their implications from language-particular and theoretical perspectives. The papers by Deborah Dahl and Thomas Rindflesch relate theoretical concepts and analyses to natural language processing. In the section on discourse, the contributions by Anita Barry and Amy Sheldon deal with interpersonal conflict; George Yule discusses the selection between direct and indirect speech forms. Helga Delisle and Cynthia Clamons consider ways in which choices among, or variation in, some grammatical and semantic categories may be explainable on pragmatic and discourse grounds. The phonology papers are focused on two major themes: underspecification and borrowing. Four of the articles address the issue of underspecification in phonological representations (Daniel Dinnsen, Joseph Stemberger, Janet Bing, Gregory Iverson). In the other two papers questions of borrowing are discussed, in Nancy Stenson's contribution from a synchronic perspective, and in Gunter Schaarsmidt's paper from a historical one. The volume is completed by a subject index and a language index.

Linguistic Structure and Change

Thomas Berg

Author : Thomas Berg
Publisher : Oxford University Press
Page : 364 pages
File Size : 42,6 Mb
Release : 1998
Category : Language Arts & Disciplines
ISBN : 0198236727

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Linguistic Structure and Change by Thomas Berg Pdf

Thomas Berg challenges context-free theories of linguistics; he is concerned with the way the term 'explanation' is typically used in the discipline. He argues that real explanations cannot emerge from a view which asserts the autonomy of language, but only from an approach which seeks to establish a connection between language and the contexts in which it is embedded. The author examines the psychological context in detail. He uses an interactiveactivation model of language processing to derive predictions about synchronic linguistic patterns, the course of linguistic change, and the structure of poetic rhymes. The majority of these predictions are borne out, leading the author to conclude that the structure of language is shaped by the properties of the mechanism which puts it to use, and that psycholinguistics thus qualifies as one likely approach from which to derive an explanation of linguistic structure.

Prediction in Second Language Processing and Learning

Edith Kaan,Theres Grüter

Author : Edith Kaan,Theres Grüter
Publisher : John Benjamins Publishing Company
Page : 250 pages
File Size : 43,8 Mb
Release : 2021-09-15
Category : Language Arts & Disciplines
ISBN : 9789027258946

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Prediction in Second Language Processing and Learning by Edith Kaan,Theres Grüter Pdf

There is ample evidence that language users, including second-language (L2) users, can predict upcoming information during listening and reading. Yet it is still unclear when, how, and why language users engage in prediction, and what the relation is between prediction and learning. This volume presents a collection of current research, insights, and directions regarding the role of prediction in L2 processing and learning. The contributions in this volume specifically address how different (L1-based) theoretical models of prediction apply to or may be expanded to account for L2 processing, report new insights on factors (linguistic, cognitive, social) that modulate L2 users’ engagement in prediction, and discuss the functions that prediction may or may not serve in L2 processing and learning. Taken together, this volume illustrates various fruitful approaches to investigating and accounting for differences in predictive processing within and across individuals, as well as across populations.

Language Down the Garden Path

Montserrat Sanz,Itziar Laka,Michael K. Tanenhaus

Author : Montserrat Sanz,Itziar Laka,Michael K. Tanenhaus
Publisher : OUP Oxford
Page : 518 pages
File Size : 43,6 Mb
Release : 2013-08-30
Category : Language Arts & Disciplines
ISBN : 9780191664823

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Language Down the Garden Path by Montserrat Sanz,Itziar Laka,Michael K. Tanenhaus Pdf

Thomas G. Bever's now iconic sentence, The horse raced past the barn fell, first appeared in his 1970 paper "The Cognitive Basis of Linguistic Structures". This 'garden path sentence', so-called because of the way it leads the reader or listener down the wrong parsing path, helped spawn the entire subfield of sentence processing. It has become the most often quoted element of a paper which spanned a wealth of research into the relationship between the grammatical system and language processing. Language Down the garden Path traces the lines of research that grew out of Bever's classic paper. Leading scientists review over 40 years of debates on the factors at play in language comprehension, production, and acquisition (the role of prediction, grammar, working memory, prosody, abstractness, syntax, and semantics mapping); the current status of universals and narrow syntax; and virtually every topic relevant in psycholinguistics since 1970. Written in an accessible and engaging style, the book will appeal to all those interested in understanding the questions that shaped, and are still shaping, this field and the ways in which linguists, cognitive scientists, psychologists, and neuroscientists are seeking to answer them.

Processing Linguistic Structure

Jesse A. Harris,Margaret Grant (Linguist)

Author : Jesse A. Harris,Margaret Grant (Linguist)
Publisher : Unknown
Page : 168 pages
File Size : 43,7 Mb
Release : 2011
Category : Psycholinguistics
ISBN : 1466369078

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Processing Linguistic Structure by Jesse A. Harris,Margaret Grant (Linguist) Pdf

University of Massachusetts Occasional Papers in Linguistics, Vol. 38: Processing Linguistic Structure

Machine Learning and Knowledge Discovery in Databases

Annalisa Appice,Pedro Pereira Rodrigues,Vítor Santos Costa,João Gama,Alípio Jorge,Carlos Soares

Author : Annalisa Appice,Pedro Pereira Rodrigues,Vítor Santos Costa,João Gama,Alípio Jorge,Carlos Soares
Publisher : Springer
Page : 773 pages
File Size : 41,9 Mb
Release : 2015-08-28
Category : Computers
ISBN : 9783319235257

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Machine Learning and Knowledge Discovery in Databases by Annalisa Appice,Pedro Pereira Rodrigues,Vítor Santos Costa,João Gama,Alípio Jorge,Carlos Soares Pdf

The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.

Structure in Language

Thomas Berg

Author : Thomas Berg
Publisher : Routledge
Page : 520 pages
File Size : 47,7 Mb
Release : 2011-01-13
Category : Language Arts & Disciplines
ISBN : 9781135852610

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Structure in Language by Thomas Berg Pdf

This book examines one of the allegedly unique features of human language: structure sensitivity. Its point of departure is the distinction between content and structural units, which are defined in psycholinguistic terms. The focus of the book is on structural representations, in particular their hierarchicalness and their branching direction. Structural representations reach variable levels of activation and are therefore gradient in nature. Their variable strength is claimed to account for numerous effects including differences between individual analytical levels, differences between languages as well as pathways of language acquisition and breakdown. English is found to be consistent in its branching direction and to have evolved its branching direction in line with the cross-level harmony constraint. Structure sensitivity is argued to be highly variable both within and across languages and consequently an unlikely candidate for a defining property of human language.

Sequences in Language and Text

George K. Mikros,Ján Macutek

Author : George K. Mikros,Ján Macutek
Publisher : Walter de Gruyter GmbH & Co KG
Page : 268 pages
File Size : 41,5 Mb
Release : 2015-04-24
Category : Language Arts & Disciplines
ISBN : 9783110394771

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Sequences in Language and Text by George K. Mikros,Ján Macutek Pdf

The edited volume Sequences in Language and Text is the first collection of original research in the area of the quantitative analysis of sequentially organized linguistic data. Linguistic sequences are extremely useful textual structures in almost all areas of Language Technology. Character and word n-grams are by far the most successful features in text classification tasks such as authorship identification, text categorization, genre classification, sentiment analysis etc. Furthermore character linguistic sequences are the basis for linguistic modeling and subsequent applications such as speech recognition, language identification etc. In addition to the above language technology oriented research, the present volume aims to give insight to the theoretical value of linguistic sequences. Sequences in texts can be produced by a number of different factors, either external to the linguistic system or by its own grammatical structure. This volume hosts contributions which will analyze linguistic sequences using quantitative methods under the synergetic theoretical framework that can explain their role in the linguistic system.

Language and Automata Theory and Applications

Shmuel Tomi Klein,Carlos Martín-Vide,Dana Shapira

Author : Shmuel Tomi Klein,Carlos Martín-Vide,Dana Shapira
Publisher : Springer
Page : 321 pages
File Size : 49,8 Mb
Release : 2018-04-03
Category : Computers
ISBN : 9783319773131

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Language and Automata Theory and Applications by Shmuel Tomi Klein,Carlos Martín-Vide,Dana Shapira Pdf

This book constitutes the refereed proceedings of the 12th International Conference on Language and Automata Theory and Applications, LATA 2018, held in Ramat Gan, Israel, in April 2018.The 20 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 58 submissions. The papers cover fields like algebraic language theory, algorithms for semi-structured data mining, algorithms on automata and words, automata and logic, automata for system analysis and programme verification, automata networks, automatic structures, codes, combinatorics on words, computational complexity, concurrency and Petri nets, data and image compression, descriptional complexity, foundations of finite state technology, foundations of XML, grammars (Chomsky hierarchy, contextual, unification, categorial, etc.), grammatical inference and algorithmic learning, graphs and graph transformation, language varieties and semigroups, language-based cryptography, mathematical and logical foundations of programming methodologies, parallel and regulated rewriting, parsing, patterns, power series, string processing algorithms, symbolic dynamics, term rewriting, transducers, trees, tree languages and tree automata, and weighted automata.

Introduction to Natural Language Processing

Jacob Eisenstein

Author : Jacob Eisenstein
Publisher : MIT Press
Page : 535 pages
File Size : 41,6 Mb
Release : 2019-10-01
Category : Computers
ISBN : 9780262042840

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Introduction to Natural Language Processing by Jacob Eisenstein Pdf

A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.

Grammatical Inference for Computational Linguistics

Jeffrey Heinz,Colin de la Higuera,Menno van Zaanen

Author : Jeffrey Heinz,Colin de la Higuera,Menno van Zaanen
Publisher : Springer Nature
Page : 139 pages
File Size : 54,8 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031021596

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Grammatical Inference for Computational Linguistics by Jeffrey Heinz,Colin de la Higuera,Menno van Zaanen Pdf

This book provides a thorough introduction to the subfield of theoretical computer science known as grammatical inference from a computational linguistic perspective. Grammatical inference provides principled methods for developing computationally sound algorithms that learn structure from strings of symbols. The relationship to computational linguistics is natural because many research problems in computational linguistics are learning problems on words, phrases, and sentences: What algorithm can take as input some finite amount of data (for instance a corpus, annotated or otherwise) and output a system that behaves "correctly" on specific tasks? Throughout the text, the key concepts of grammatical inference are interleaved with illustrative examples drawn from problems in computational linguistics. Special attention is paid to the notion of "learning bias." In the context of computational linguistics, such bias can be thought to reflect common (ideally universal) properties of natural languages. This bias can be incorporated either by identifying a learnable class of languages which contains the language to be learned or by using particular strategies for optimizing parameter values. Examples are drawn largely from two linguistic domains (phonology and syntax) which span major regions of the Chomsky Hierarchy (from regular to context-sensitive classes). The conclusion summarizes the major lessons and open questions that grammatical inference brings to computational linguistics. Table of Contents: List of Figures / List of Tables / Preface / Studying Learning / Formal Learning / Learning Regular Languages / Learning Non-Regular Languages / Lessons Learned and Open Problems / Bibliography / Author Biographies

Linguistic Structure Prediction

Linguistic Structure Prediction by Noah A. Smith Pdf

Linguistic Structure Prediction by Noah A. Smith Pdf

Computational Modeling of Human Language Acquisition by Afra Alishahi,Bing Liu,Inderjeet Mani,Jörg Tiedemann,Manfred Stede,Noah A. Smith Pdf

Advanced Structured Prediction by Sebastian Nowozin,Peter V. Gehler,Jeremy Jancsary,Christoph H. Lampert Pdf

Principles and Prediction by Mushira Eid,Gregory K. Iverson Pdf

Linguistic Structure and Change by Thomas Berg Pdf

Prediction in Second Language Processing and Learning by Edith Kaan,Theres Grüter Pdf

Language Down the Garden Path by Montserrat Sanz,Itziar Laka,Michael K. Tanenhaus Pdf

Processing Linguistic Structure by Jesse A. Harris,Margaret Grant (Linguist) Pdf

Machine Learning and Knowledge Discovery in Databases by Annalisa Appice,Pedro Pereira Rodrigues,Vítor Santos Costa,João Gama,Alípio Jorge,Carlos Soares Pdf

Structure in Language by Thomas Berg Pdf

Sequences in Language and Text by George K. Mikros,Ján Macutek Pdf

Language and Automata Theory and Applications by Shmuel Tomi Klein,Carlos Martín-Vide,Dana Shapira Pdf

Introduction to Natural Language Processing by Jacob Eisenstein Pdf

Grammatical Inference for Computational Linguistics by Jeffrey Heinz,Colin de la Higuera,Menno van Zaanen Pdf

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