Approaches To Natural Language
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Approaches To Natural Language
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Author : Jaakko Hintikka
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Approaches To Natural Language written by Jaakko Hintikka and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Philosophy categories.
The papers and comments published in the present volume represent the proceedings of a research workshop on the grammar and semantics of natural languages held at Stanford University in the fall of 1970. The workshop met first for three days in September and then for a period of two days in November for extended discussion and analysis. The workshop was sponsored by the Committee on Basic Research in Education, which has been funded by the United States Office of Education through a grant to the National Academy of Education and the National Academy of Sciences - National Research Council. We acknowledge with pleasure the sponsorship which made possible a series oflively and stimulating meetings that were both enjoyable and instructive for the three of us, and, we hope, for most of the participants, including a number of local linguists and philosophers who did not contribute papers but actively joined in the discussion. One of the central participants in the workshop was Richard Montague. We record our sense of loss at his tragic death early in 1971, and we dedicate this volume to his memory. None of the papers in the present volume discusses explicitly problems of education. In our view such a discussion is neither necessary nor sufficient for a contribution to basic research in education. There are in fact good reasons why the kind of work reported in the present volume constitutes an important aspect of basic research in education.
Cognitive Approach To Natural Language Processing
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Author : Bernadette Sharp
language : en
Publisher: Elsevier
Release Date : 2017-05-31
Cognitive Approach To Natural Language Processing written by Bernadette Sharp and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-31 with Computers categories.
As natural language processing spans many different disciplines, it is sometimes difficult to understand the contributions and the challenges that each of them presents. This book explores the special relationship between natural language processing and cognitive science, and the contribution of computer science to these two fields. It is based on the recent research papers submitted at the international workshops of Natural Language and Cognitive Science (NLPCS) which was launched in 2004 in an effort to bring together natural language researchers, computer scientists, and cognitive and linguistic scientists to collaborate together and advance research in natural language processing. The chapters cover areas related to language understanding, language generation, word association, word sense disambiguation, word predictability, text production and authorship attribution. This book will be relevant to students and researchers interested in the interdisciplinary nature of language processing. - Discusses the problems and issues that researchers face, providing an opportunity for developers of NLP systems to learn from cognitive scientists, cognitive linguistics and neurolinguistics - Provides a valuable opportunity to link the study of natural language processing to the understanding of the cognitive processes of the brain
Neural Network Methods For Natural Language Processing
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Author : Yoav Goldberg
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Neural Network Methods For Natural Language Processing written by Yoav Goldberg and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
Speech And Language Processing
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Author : Daniel Jurafsky
language : en
Publisher:
Release Date : 2000-01
Speech And Language Processing written by Daniel Jurafsky and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01 with Automatic speech recognition categories.
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
Practical Natural Language Processing
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Author : Sowmya Vajjala
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-17
Practical Natural Language Processing written by Sowmya Vajjala and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-17 with Computers categories.
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
Introduction To Natural Language Processing
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Author : Jacob Eisenstein
language : en
Publisher: MIT Press
Release Date : 2019-10-01
Introduction To Natural Language Processing written by Jacob Eisenstein and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-01 with Computers categories.
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.
Logic As Grammar
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Author : Norbert Hornstein
language : en
Publisher: MIT Press
Release Date : 1984
Logic As Grammar written by Norbert Hornstein and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Language Arts & Disciplines categories.
How is the meaning of natural language interpreted? Taking as its point of departure the logical problem of natural language acquisition, this book elaborates a theory of meaning based on syntactical rather than semantical processes. Copyright © Libri GmbH. All rights reserved.
Natural Language Processing
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Author : Epaminondas Kapetanios
language : en
Publisher: CRC Press
Release Date : 2013-11-14
Natural Language Processing written by Epaminondas Kapetanios and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-14 with Computers categories.
This book introduces the semantic aspects of natural language processing and its applications. Topics covered include: measuring word meaning similarity, multi-lingual querying, and parametric theory, named entity recognition, semantics, query language, and the nature of language. The book also emphasizes the portions of mathematics needed to understand the discussed algorithms.
Deep Learning For Natural Language Processing
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Author : Stephan Raaijmakers
language : en
Publisher: Simon and Schuster
Release Date : 2022-12-06
Deep Learning For Natural Language Processing written by Stephan Raaijmakers and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-06 with Computers categories.
Explore the most challenging issues of natural language processing, and learn how to solve them with cutting-edge deep learning! Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You'll learn to use state-of the-art tools and techniques including BERT and XLNET, multitask learning, and deep memory-based NLP. Fascinating examples give you hands-on experience with a variety of real world NLP applications. Plus, the detailed code discussions show you exactly how to adapt each example to your own uses!
Natural Language Processing For Corpus Linguistics
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Author : Jonathan Dunn
language : en
Publisher: Cambridge University Press
Release Date : 2022-03-31
Natural Language Processing For Corpus Linguistics written by Jonathan Dunn and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-31 with Language Arts & Disciplines categories.
Corpus analysis can be expanded and scaled up by incorporating computational methods from natural language processing. This Element shows how text classification and text similarity models can extend our ability to undertake corpus linguistics across very large corpora. These computational methods are becoming increasingly important as corpora grow too large for more traditional types of linguistic analysis. We draw on five case studies to show how and why to use computational methods, ranging from usage-based grammar to authorship analysis to using social media for corpus-based sociolinguistics. Each section is accompanied by an interactive code notebook that shows how to implement the analysis in Python. A stand-alone Python package is also available to help readers use these methods with their own data. Because large-scale analysis introduces new ethical problems, this Element pairs each new methodology with a discussion of potential ethical implications.