Theoretical Issues in Natural Language Processing
Theoretical Issues in Natural Language Processing

Author: Yorick Wilks

Publisher: Psychology Press

Published: 2018-10-24

Total Pages: 227

ISBN-13: 1317717554

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Accompanying continued industrial production and sales of artificial intelligence and expert systems is the risk that difficult and resistant theoretical problems and issues will be ignored. The participants at the Third Tinlap Workshop, whose contributions are contained in Theoretical Issues in Natural Language Processing, remove that risk. They discuss and promote theoretical research on natural language processing, examinations of solutions to current problems, development of new theories, and representations of published literature on the subject. Discussions among these theoreticians in artificial intelligence, logic, psychology, philosophy, and linguistics draw a comprehensive, up-to-date picture of the natural language processing field.

Embeddings in Natural Language Processing
Embeddings in Natural Language Processing

Author: Mohammad Taher Pilehvar

Publisher: Morgan & Claypool Publishers

Published: 2020-11-13

Total Pages: 177

ISBN-13: 1636390226

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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.

Foundational Issues in Natural Language Processing
Foundational Issues in Natural Language Processing

Author: Peter Sells

Publisher: Bradford Book

Published: 1991

Total Pages: 248

ISBN-13:

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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.

Recent Advances in Natural Language Processing III
Recent Advances in Natural Language Processing III

Author: Nicolas Nicolov

Publisher: John Benjamins Publishing

Published: 2004-11-30

Total Pages: 418

ISBN-13: 9027294682

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This volume brings together revised versions of a selection of papers presented at the 2003 International Conference on “Recent Advances in Natural Language Processing”. A wide range of topics is covered in the volume: semantics, dialogue, summarization, anaphora resolution, shallow parsing, morphology, part-of-speech tagging, named entity, question answering, word sense disambiguation, information extraction. Various ‘state-of-the-art’ techniques are explored: finite state processing, machine learning (support vector machines, maximum entropy, decision trees, memory-based learning, inductive logic programming, transformation-based learning, perceptions), latent semantic analysis, constraint programming. The papers address different languages (Arabic, English, German, Slavic languages) and use different linguistic frameworks (HPSG, LFG, constraint-based DCG). This book will be of interest to those who work in computational linguistics, corpus linguistics, human language technology, translation studies, cognitive science, psycholinguistics, artificial intelligence, and informatics.

Strategies for Natural Language Processing
Strategies for Natural Language Processing

Author: W. G. Lehnert

Publisher: Psychology Press

Published: 2014-04-04

Total Pages: 556

ISBN-13: 1317769252

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First published in 1982. Simply defined, the field of natural language processing is concerned with theories and techniques that address the problem of natural language communication with computers. One of the goals of this research is to design computer programs that will allow people to interact with computers in natural conversational dialogues.

Natural Language Processing in Artificial Intelligence
Natural Language Processing in Artificial Intelligence

Author: Brojo Kishore Mishra

Publisher: CRC Press

Published: 2020-11-01

Total Pages: 297

ISBN-13: 1000711315

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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.

Hybrid Approaches to Machine Translation
Hybrid Approaches to Machine Translation

Author: Marta R. Costa-jussà

Publisher: Springer

Published: 2016-07-12

Total Pages: 208

ISBN-13: 3319213113

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This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are achieved by combining data-driven and rule-based techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical approaches to MT, the incorporation of data-driven components into rule-based approaches, or statistical and rule-based pre- and post-processing for both types of MT architectures. The book is of interest primarily to MT specialists, but also – in the wider fields of Computational Linguistics, Machine Learning and Data Mining – to translators and managers of translation companies and departments who are interested in recent developments concerning automated translation tools.

The Semantic Representation of Natural Language
The Semantic Representation of Natural Language

Author: Michael Levison

Publisher: A&C Black

Published: 2012-12-20

Total Pages: 304

ISBN-13: 1441190732

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This volume contains a detailed, precise and clear semantic formalism designed to allow non-programmers such as linguists and literary specialists to represent elements of meaning which they must deal with in their research and teaching. At the same time, by its basis in a functional programming paradigm, it retains sufficient formal precision to support computational implementation. The formalism is designed to represent meaning as found at a variety of levels, including basic semantic units and relations, word meaning, sentence-level phenomena, and text-level meaning. By drawing on fundamental principles of program design, the proposed formalism is both easy to read and modify yet sufficiently powerful to allow for the representation of complex semantic phenomena. In this monograph, the authors introduce the formalism and show its basic structure, apply it to the analysis of the semantics of a variety of linguistic phenomena in both English and French, and use it to represent the semantics of a variety of texts ranging from single sentences, to textual excepts, to a full story.

Cognitive Approach to Natural Language Processing
Cognitive Approach to Natural Language Processing

Author: Bernadette Sharp

Publisher: Elsevier

Published: 2017-05-31

Total Pages: 236

ISBN-13: 008102343X

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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