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Author: Georgia M. Green
Publisher: Routledge
ISBN: 1136492828
Category : Language Arts & Disciplines
Languages : en
Pages : 203
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Book Description
This book differs from other introductions to pragmatics in approaching the problems of interpreting language use in terms of interpersonal modelling of beliefs and intentions. It is intended to make issues involved in language understanding, such as speech, text, and discourse, accessible to the widest group possible -- not just specialists in linguistics or communication theorists -- but all scholars and researchers whose enterprises depend on having a useful model of how communicative agents understand utterances and expect their own utterances to be understood. Based on feedback from readers over the past seven years, explanations in every chapter have been improved and updated in this thoroughly revised version of the original text published in 1989. The most extensive revisions concern the relevance of technical notions of mutual and normal belief, and the futility of using the notion 'null context' to describe meaning. In addition, the discussion of implicature now includes an extended explication of "Grice's Cooperative Principle" which attempts to put it in the context of his theory of meaning and rationality, and to preclude misinterpretations which it has suffered over the past 20 years. The revised chapter exploits the notion of normal belief to improve the account of conversational implicature.
Author: Georgia M. Green
Publisher: Routledge
ISBN: 1136492828
Category : Language Arts & Disciplines
Languages : en
Pages : 203
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Book Description
This book differs from other introductions to pragmatics in approaching the problems of interpreting language use in terms of interpersonal modelling of beliefs and intentions. It is intended to make issues involved in language understanding, such as speech, text, and discourse, accessible to the widest group possible -- not just specialists in linguistics or communication theorists -- but all scholars and researchers whose enterprises depend on having a useful model of how communicative agents understand utterances and expect their own utterances to be understood. Based on feedback from readers over the past seven years, explanations in every chapter have been improved and updated in this thoroughly revised version of the original text published in 1989. The most extensive revisions concern the relevance of technical notions of mutual and normal belief, and the futility of using the notion 'null context' to describe meaning. In addition, the discussion of implicature now includes an extended explication of "Grice's Cooperative Principle" which attempts to put it in the context of his theory of meaning and rationality, and to preclude misinterpretations which it has suffered over the past 20 years. The revised chapter exploits the notion of normal belief to improve the account of conversational implicature.
Author: Georgia M. Green
Publisher: Psychology Press
ISBN: 0805821651
Category : Cognitive science
Languages : en
Pages : 203
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Book Description
First Published in 1996. Routledge is an imprint of Taylor & Francis, an informa company.
Author: Emily M. Bender
Publisher: Morgan & Claypool Publishers
ISBN: 168173074X
Category : Computers
Languages : en
Pages : 270
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Book Description
Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of both Natural Language Understanding (NLU) and Natural Language Generation (NLG). This is because the aims of these fields are to build systems that understand what people mean when they speak or write, and that can produce linguistic strings that successfully express to people the intended content. In order for NLP to scale beyond partial, task-specific solutions, researchers in these fields must be informed by what is known about how humans use language to express and understand communicative intents. The purpose of this book is to present a selection of useful information about semantics and pragmatics, as understood in linguistics, in a way that's accessible to and useful for NLP practitioners with minimal (or even no) prior training in linguistics.
Author: Emily M. Bender
Publisher: Morgan & Claypool Publishers
ISBN: 1627050124
Category : Computers
Languages : en
Pages : 186
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Book Description
Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages
Author: Sowmya Vajjala
Publisher: O'Reilly Media
ISBN: 149205402X
Category : Computers
Languages : en
Pages : 455
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Book Description
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective
Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912
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Book Description
Author: Christopher Manning
Publisher: MIT Press
ISBN: 0262303795
Category : Language Arts & Disciplines
Languages : en
Pages : 719
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Book Description
Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.
Author: Jacob Eisenstein
Publisher: MIT Press
ISBN: 0262354578
Category : Computers
Languages : en
Pages : 536
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Book Description
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.
Author: Alex Thomas
Publisher: O'Reilly Media
ISBN: 1492047732
Category : Computers
Languages : en
Pages : 367
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Book Description
If you want to build an enterprise-quality application that uses natural language text but aren’t sure where to begin or what tools to use, this practical guide will help get you started. Alex Thomas, principal data scientist at Wisecube, shows software engineers and data scientists how to build scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library. Through concrete examples, practical and theoretical explanations, and hands-on exercises for using NLP on the Spark processing framework, this book teaches you everything from basic linguistics and writing systems to sentiment analysis and search engines. You’ll also explore special concerns for developing text-based applications, such as performance. In four sections, you’ll learn NLP basics and building blocks before diving into application and system building: Basics: Understand the fundamentals of natural language processing, NLP on Apache Stark, and deep learning Building blocks: Learn techniques for building NLP applications—including tokenization, sentence segmentation, and named-entity recognition—and discover how and why they work Applications: Explore the design, development, and experimentation process for building your own NLP applications Building NLP systems: Consider options for productionizing and deploying NLP models, including which human languages to support
Author: Kevin Bretonnel Cohen
Publisher: John Benjamins Publishing Company
ISBN: 9027271062
Category : Computers
Languages : en
Pages : 174
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Book Description
Biomedical Natural Language Processing is a comprehensive tour through the classic and current work in the field. It discusses all subjects from both a rule-based and a machine learning approach, and also describes each subject from the perspective of both biological science and clinical medicine. The intended audience is readers who already have a background in natural language processing, but a clear introduction makes it accessible to readers from the fields of bioinformatics and computational biology, as well. The book is suitable as a reference, as well as a text for advanced courses in biomedical natural language processing and text mining.
