Representation And Inference For Natural Language
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Representation And Inference For Natural Language
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Author : Patrick Blackburn
language : en
Publisher:
Release Date : 1998
Representation And Inference For Natural Language written by Patrick Blackburn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
Representation And Inference For Natural Language
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Author : Patrick Blackburn
language : en
Publisher: Center for the Study of Language and Information Publica Tion
Release Date : 2005
Representation And Inference For Natural Language written by Patrick Blackburn and has been published by Center for the Study of Language and Information Publica Tion this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computational linguistics categories.
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.
Representation Learning For Natural Language Processing
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Author : Zhiyuan Liu
language : en
Publisher: Springer Nature
Release Date : 2020-07-03
Representation Learning For Natural Language Processing written by Zhiyuan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-03 with Computers categories.
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.
Diagrammatic Representation And Inference
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Author : Jens Lemanski
language : en
Publisher: Springer Nature
Release Date : 2024-09-08
Diagrammatic Representation And Inference written by Jens Lemanski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-08 with Computers categories.
This book constitutes the refereed proceedings of the 14th International Conference on the Theory and Application of Diagrams, Diagrams 2024, held in Münster, Germany, during September 27–October 1, 2024. The 17 full papers, 19 short papers and 11 papers of other types included in this book were carefully reviewed and selected from 69 submissions. They were organized in topical sections as follows: Keynote Talks; Analysis of Diagrams; Euler and Venn Diagrams; Diagrams in Logic; Diagrams and Applications; Diagram Tools; Historical Aspects of Diagrams; and Posters.
Diagrammatic Representation And Inference
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Author : Tim Dwyer
language : en
Publisher: Springer
Release Date : 2014-07-23
Diagrammatic Representation And Inference written by Tim Dwyer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-23 with Computers categories.
This book constitutes the refereed proceedings of the 8th International Conference on the Theory and Application of Diagrams, Diagrams 2014, held in Melbourne, VIC, Australia in July/August 2014. The 15 revised full papers and 9 short papers presented together with 6 posters were carefully reviewed and selected from 40 submissions. The papers have been organized in the following topical sections: diagram layout, diagram notations, diagramming tools, diagrams in education, empirical studies and logic and diagrams.
Recent Advances In Natural Language Processing V
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Author : Nicolas Nicolov
language : en
Publisher: John Benjamins Publishing
Release Date : 2009
Recent Advances In Natural Language Processing V written by Nicolas Nicolov and has been published by John Benjamins Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Language Arts & Disciplines categories.
Linguistics, Corpus Linguistics, and Machine Translation." --Book Jacket.
Computational Linguistics And Intelligent Text Processing
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Author : Alexander Gelbukh
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-02-08
Computational Linguistics And Intelligent Text Processing written by Alexander Gelbukh 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 2008-02-08 with Computers categories.
This book constitutes the refereed proceedings of the 9th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2008, held in Haifa, Israel, in February 2008. The 52 revised full papers presented together with 4 invited papers were carefully reviewed and selected from numerous submissions. The papers cover all current issues in computational linguistics research and present intelligent text processing applications. The papers are organized in topical sections on language resources, morphology and syntax, semantics and discourse, word sense disambiguation and named entity recognition, anaphora and co-reference, machine translation and parallel corpora, natural language generation, speech recognition, information retrieval and question answering, text classification, text summarization, as well as spell checking and authoring aid.
Natural Language Processing With Pytorch
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Author : Delip Rao
language : en
Publisher: O'Reilly Media
Release Date : 2019-01-22
Natural Language Processing With Pytorch written by Delip Rao 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 2019-01-22 with Computers categories.
Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems
Graph Learning And Network Science For Natural Language Processing
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Author : Muskan Garg
language : en
Publisher: CRC Press
Release Date : 2022-12-28
Graph Learning And Network Science For Natural Language Processing written by Muskan Garg and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-28 with Business & Economics categories.
Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.