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Author: Patrick Blackburn
Publisher: Center for the Study of Language and Information Publica Tion
ISBN: 9781575864969
Category : Computational linguistics
Languages : en
Pages : 0
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Book Description
How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.
Author: Patrick Blackburn
Publisher: Center for the Study of Language and Information Publica Tion
ISBN: 9781575864969
Category : Computational linguistics
Languages : en
Pages : 0
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Book Description
How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.
Author: Zhiyuan Liu
Publisher: Springer Nature
ISBN: 9811555737
Category : Computers
Languages : en
Pages : 319
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Book Description
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
Author: Mohammad Taher Pilehvar
Publisher: Morgan & Claypool Publishers
ISBN: 1636390226
Category : Computers
Languages : en
Pages : 177
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Book Description
Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.
Author: Łucja M. Iwańska
Publisher: AAAI Press
ISBN:
Category : Computers
Languages : en
Pages : 490
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Book Description
"Traditionally, knowledge representation and reasoning systems have incorporated natural language as interfaces to expert systems or knowledge bases that performed tasks separate from natural language processing. As this book shows, however, the computational nature of representation and inference in natural language makes it the ideal model for all tasks in an intelligent computer system. Natural language processing combines the qualitative characteristics of human knowledge processing with a computer's quantitative advantages, allowing for in-depth, systematic processing of vast amounts of information.
Author: Douglas B. Lenat
Publisher: Addison Wesley Publishing Company
ISBN:
Category : Computers
Languages : en
Pages : 408
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Book Description
Chapter one presents the Cyc "philosophy" or paradigm. Chapter 2 presents a global overview of Cyc, including its representation language, the ontology f its knowledge base, and teh environment which it functions. Chapter 3 goes into much more detail on the representation language, including the structure and function of Cyc's metalevel agenda mechanism. Chapter 4 presents heuristics for ontological engineering, the pricnples upon whcihc Cyc's ontology is based. Chapter 5 the provides a glimpse into the global ontology of knowledge. Chapter 6 explains how we "solve" (i.e., adequately handle) the various tough representation thorns (substances, time, space, structures, composite mental/physical objects, beliefs, uncertainty, etc. ). Chapter 7 surveys the mistakes that new knowledge tnereres most often commit. Chapter 8, the concluding chapter, includes a brief status report on the project, and a statement of goals and a timetable for the coming five years.
Author: Ernest LePore
Publisher:
ISBN: 0198717180
Category : Language Arts & Disciplines
Languages : en
Pages : 305
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Book Description
How do hearers manage to understand speakers? And how do speakers manage to shape hearers' understanding? Lepore and Stone show that standard views about the workings of semantics and pragmatics are unsatisfactory. They advance an alternative view which better captures what is going on in linguistic communication.
Author: Jerry Bobrow
Publisher: Elsevier
ISBN: 1483299155
Category : Computers
Languages : en
Pages : 442
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Book Description
Representation and Understanding
Author: Yoav Goldberg
Publisher: Morgan & Claypool Publishers
ISBN: 162705295X
Category : Computers
Languages : en
Pages : 311
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Book Description
Neural networks are a family of powerful machine learning models and this book focuses on their application 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.
Author: Jan van Eijck
Publisher: Cambridge University Press
ISBN: 1139490907
Category : Language Arts & Disciplines
Languages : en
Pages : 422
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Book Description
Computational semantics is the art and science of computing meaning in natural language. The meaning of a sentence is derived from the meanings of the individual words in it, and this process can be made so precise that it can be implemented on a computer. Designed for students of linguistics, computer science, logic and philosophy, this comprehensive text shows how to compute meaning using the functional programming language Haskell. It deals with both denotational meaning (where meaning comes from knowing the conditions of truth in situations), and operational meaning (where meaning is an instruction for performing cognitive action). Including a discussion of recent developments in logic, it will be invaluable to linguistics students wanting to apply logic to their studies, logic students wishing to learn how their subject can be applied to linguistics, and functional programmers interested in natural language processing as a new application area.
Author: Jacob Eisenstein
Publisher: MIT Press
ISBN: 0262042843
Category : Computers
Languages : en
Pages : 535
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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.
