Foundational Issues in Natural Language Processing PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Foundational Issues in Natural Language Processing PDF full book. Access full book title Foundational Issues in Natural Language Processing by Peter Sells. Download full books in PDF and EPUB format.
Author: Peter Sells
Publisher: Bradford Book
ISBN:
Category : Computers
Languages : en
Pages : 248
Get Book Here
Book Description
Four separate essays address the complex and difficult connections among grammatical theory, mathematical linguistics, and the operation of real natural-language-processing systems, both human and electronic.William Rounds, Avarind Joshi, Janet Fodor, and Robert Berwick are leading scholars in the multidisciplinary field of natural language processing. In four separate essays they address the complex and difficult connections among grammatical theory, mathematical linguistics, and the operation of real natural-language-processing systems, both human and electronic. The editors' substantial introduction details the progress and problems involved in attempts to relate these four areas of research. William Rounds discusses the relevance of complexity results to linguistics and computational linguistics, providing useful caveats about how results might be misinterpreted and pointing out promising avenues of future research. Avarind Joshi (with K. Vijay-Shanker and David Weir) surveys results showing the equivalence of several different grammatical formalisms, all of which are mildly context-sensitive, with special attention to variants of tree adjoining grammar. Janet Fodor discusses how psycholinguistic results can bear on the choice among competing grammatical theories, surveying a number of recent experiments and their relevance to issues in grammatical theory. Robert Berwick considers the relationship between issues in linguistic theory and the construction of computational parsing systems, in particular the question of what it means to implement a theory of grammar in a computational system. He argues for the advantages of a principle-based approach over a rule-based one, and surveys several recent parsing systems based on the theory of government and binding.
Author: Peter Sells
Publisher: Bradford Book
ISBN:
Category : Computers
Languages : en
Pages : 248
Get Book Here
Book Description
Four separate essays address the complex and difficult connections among grammatical theory, mathematical linguistics, and the operation of real natural-language-processing systems, both human and electronic.William Rounds, Avarind Joshi, Janet Fodor, and Robert Berwick are leading scholars in the multidisciplinary field of natural language processing. In four separate essays they address the complex and difficult connections among grammatical theory, mathematical linguistics, and the operation of real natural-language-processing systems, both human and electronic. The editors' substantial introduction details the progress and problems involved in attempts to relate these four areas of research. William Rounds discusses the relevance of complexity results to linguistics and computational linguistics, providing useful caveats about how results might be misinterpreted and pointing out promising avenues of future research. Avarind Joshi (with K. Vijay-Shanker and David Weir) surveys results showing the equivalence of several different grammatical formalisms, all of which are mildly context-sensitive, with special attention to variants of tree adjoining grammar. Janet Fodor discusses how psycholinguistic results can bear on the choice among competing grammatical theories, surveying a number of recent experiments and their relevance to issues in grammatical theory. Robert Berwick considers the relationship between issues in linguistic theory and the construction of computational parsing systems, in particular the question of what it means to implement a theory of grammar in a computational system. He argues for the advantages of a principle-based approach over a rule-based one, and surveys several recent parsing systems based on the theory of government and binding.
Author: Christopher Manning
Publisher: MIT Press
ISBN: 0262303795
Category : Language Arts & Disciplines
Languages : en
Pages : 719
Get Book Here
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: Madeleine Bates
Publisher: Cambridge University Press
ISBN: 0521410150
Category : Computers
Languages : en
Pages : 312
Get Book Here
Book Description
This book addresses theoretical or applied work in the field of natural language processing.
Author: Yue Zhang
Publisher: Cambridge University Press
ISBN: 1108420214
Category : Computers
Languages : en
Pages : 487
Get Book Here
Book Description
This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.
Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912
Get Book Here
Book Description
Author: Jacob Eisenstein
Publisher: MIT Press
ISBN: 0262042843
Category : Computers
Languages : en
Pages : 535
Get Book Here
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: Sowmya Vajjala
Publisher: O'Reilly Media
ISBN: 149205402X
Category : Computers
Languages : en
Pages : 455
Get Book Here
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: Yorick Wilks
Publisher: Now Publishers Inc
ISBN: 1601982100
Category : Computers
Languages : en
Pages : 141
Get Book Here
Book Description
Looks at how Natural language Processing underpins the Semantic Web, including its initial construction from unstructured sources like the World Wide Web.
Author: Brojo Kishore Mishra
Publisher: CRC Press
ISBN: 1000711315
Category : Science
Languages : en
Pages : 297
Get Book Here
Book Description
This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.
Author: Gerhard Paaß
Publisher: Springer Nature
ISBN: 3031231902
Category : Computers
Languages : en
Pages : 448
Get Book Here
Book Description
This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models. After a brief introduction to basic NLP models the main pre-trained language models BERT, GPT and sequence-to-sequence transformer are described, as well as the concepts of self-attention and context-sensitive embedding. Then, different approaches to improving these models are discussed, such as expanding the pre-training criteria, increasing the length of input texts, or including extra knowledge. An overview of the best-performing models for about twenty application areas is then presented, e.g., question answering, translation, story generation, dialog systems, generating images from text, etc. For each application area, the strengths and weaknesses of current models are discussed, and an outlook on further developments is given. In addition, links are provided to freely available program code. A concluding chapter summarizes the economic opportunities, mitigation of risks, and potential developments of AI.
