New Concepts in Natural Language Generation PDF Download

Author: Helmut Horacek
Publisher: Bloomsbury Publishing
ISBN: 1474246427
Category : Language Arts & Disciplines
Languages : en
Pages : 336

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Book Description
This book aims to inform researchers with an interest in natural language generation about advances in the field. It is organised around four topics – system architectures, content planning, discourse planning and realisation in linguistic form - and it presents some of the most important works in this area of research.

Author: Bandyopadhyay, Sivaji
Publisher: IGI Global
ISBN: 1466621702
Category : Computers
Languages : en
Pages : 389

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Book Description
"This book provides pertinent and vital information that researchers, postgraduate, doctoral students, and practitioners are seeking for learning about the latest discoveries and advances in NLP methodologies and applications of NLP"--Provided by publisher.

Author: Giovanni Adorni
Publisher: Springer Science & Business Media
ISBN: 9783540608004
Category : Computers
Languages : en
Pages : 402

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Book Description
This proceedings volume gives an up-to-date overview of the most recent results in the field of plant molecular response to environmental constraints, especially heat, cold, water/drought, salt or light. It centers on molecular approaches in understanding the bases of plant tolerance to physical stresses, links among different environmental stresses, and the manipulation of gene expression by recombinant DNA technology to obtain tolerant transgenic plants.

Author: Amanda Stent
Publisher: Cambridge University Press
ISBN: 1107010020
Category : Computers
Languages : en
Pages : 383

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Book Description
A comprehensive overview of the state-of-the-art in natural language generation for interactive systems, with links to resources for further research.

Author: Ehud Reiter
Publisher: Cambridge University Press
ISBN: 0521620368
Category : Computers
Languages : en
Pages : 274

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Book Description
This book explains how to build Natural Language Generation (NLG) systems - computer software systems which use techniques from artificial intelligence and computational linguistics to automatically generate understandable texts in English or other human languages, either in isolation or as part of multimedia documents, Web pages, and speech output systems. Typically starting from some non-linguistic representation of information as input, NLG systems use knowledge about language and the application domain to automatically produce documents, reports, explanations, help messages, and other kinds of texts. The book covers the algorithms and representations needed to perform the core tasks of document planning, microplanning, and surface realization, using a case study to show how these components fit together. It also discusses engineering issues such as system architecture, requirements analysis, and the integration of text generation into multimedia and speech output systems.

Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1799809528
Category : Computers
Languages : en
Pages : 1704

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Book Description
As technology continues to become more sophisticated, a computer’s ability to understand, interpret, and manipulate natural language is also accelerating. Persistent research in the field of natural language processing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror natural language processes that have existed for centuries. Natural Language Processing: Concepts, Methodologies, Tools, and Applications is a vital reference source on the latest concepts, processes, and techniques for communication between computers and humans. Highlighting a range of topics such as machine learning, computational linguistics, and semantic analysis, this multi-volume book is ideally designed for computer engineers, computer and software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of natural language processing.

Author: G.A. Kempen
Publisher: Springer
ISBN: 9024735580
Category : Computers
Languages : en
Pages : 466

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Book Description
Authors and Participants xi I Pragmatic Aspects 1 1. Some pragmatic decision criteria in generation 3 EduardH. Hovy 2. How to appear to be conforming to the 'maxims' even if you prefer to violate them 19 Antlwny Jameson 43 3. Contextual effects on responses to misconceptions Kathleen F. McCoy 4. Generating understandable explanatory sentences 55 Domenico Parisi & Donatella Ferrante 5. Toward a plan-based theory of referring actions 63 Douglas E. Appelt Generating referring expressions and pointing gestures 71 6. Norben Reithinger II Generation of Connected Discourse 83 7. Rhetorical Structure Theory: description and construction of text structures 85 William C. Mann & Sandra A. Tlwmpson 8. Discourse strategies for describing complex physical objects 97 Cecile L. Paris & Kathleen R. McKeown 9. Strategies for generating coherent descriptions of object movements in street scenes 117 Hans-Joachim Novak 133 10. The automated news agency: SEMTEX - a text generator for German Dietmar ROsner 149 11. A connectionist approach to the generation of abstracts KOiti Hasida, Shun Ishizald & Hitoshi Isahara III Generator Design 157 159 12. Factors contributing to efficiency in natural language generation DavidD. McDonald, Marie M. Vaughan & James D. Pustejovsky 183 13. Reviewing as a component of the text generation process Masoud Yazdani A French and English syntactic component for generation 191 14. Laurence Danlos KING: a knowledge-intensive natural language generator 219 15. Paul S. Jacobs vii 231 IV Grammars and Grammatical Formalisms 233 16. The relevance of Tree Adjoining Grammar to generation Aravind K.

Author: Denis Rothman
Publisher: Packt Publishing Ltd
ISBN: 1800568630
Category : Computers
Languages : en
Pages : 385

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Book Description
Publisher's Note: A new edition of this book is out now that includes working with GPT-3 and comparing the results with other models. It includes even more use cases, such as casual language analysis and computer vision tasks, as well as an introduction to OpenAI's Codex. Key FeaturesBuild and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using concepts that outperform classical deep learning modelsGo through hands-on applications in Python using Google Colaboratory Notebooks with nothing to install on a local machineTest transformer models on advanced use casesBook Description The transformer architecture has proved to be revolutionary in outperforming the classical RNN and CNN models in use today. With an apply-as-you-learn approach, Transformers for Natural Language Processing investigates in vast detail the deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question answering, and many more NLP domains with transformers. The book takes you through NLP with Python and examines various eminent models and datasets within the transformer architecture created by pioneers such as Google, Facebook, Microsoft, OpenAI, and Hugging Face. The book trains you in three stages. The first stage introduces you to transformer architectures, starting with the original transformer, before moving on to RoBERTa, BERT, and DistilBERT models. You will discover training methods for smaller transformers that can outperform GPT-3 in some cases. In the second stage, you will apply transformers for Natural Language Understanding (NLU) and Natural Language Generation (NLG). Finally, the third stage will help you grasp advanced language understanding techniques such as optimizing social network datasets and fake news identification. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models by tech giants to various datasets. What you will learnUse the latest pretrained transformer modelsGrasp the workings of the original Transformer, GPT-2, BERT, T5, and other transformer modelsCreate language understanding Python programs using concepts that outperform classical deep learning modelsUse a variety of NLP platforms, including Hugging Face, Trax, and AllenNLPApply Python, TensorFlow, and Keras programs to sentiment analysis, text summarization, speech recognition, machine translations, and moreMeasure the productivity of key transformers to define their scope, potential, and limits in productionWho this book is for Since the book does not teach basic programming, you must be familiar with neural networks, Python, PyTorch, and TensorFlow in order to learn their implementation with Transformers. Readers who can benefit the most from this book include experienced deep learning & NLP practitioners and data analysts & data scientists who want to process the increasing amounts of language-driven data.

Author: Sowmya Vajjala
Publisher: O'Reilly Media
ISBN: 149205402X
Category : Computers
Languages : en
Pages : 455

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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: Ankur A. Patel
Publisher: "O'Reilly Media, Inc."
ISBN: 1492062529
Category : Computers
Languages : en
Pages : 330

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Book Description
NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production