Download or read book Integration of World Knowledge for Natural Language Understanding written by Ekaterina Ovchinnikova and published by Springer Science & Business Media. This book was released on 2012-02-15 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concerns non-linguistic knowledge required to perform computational natural language understanding (NLU). The main objective of the book is to show that inference-based NLU has the potential for practical large scale applications. First, an introduction to research areas relevant for NLU is given. We review approaches to linguistic meaning, explore knowledge resources, describe semantic parsers, and compare two main forms of inference: deduction and abduction. In the main part of the book, we propose an integrative knowledge base combining lexical-semantic, ontological, and distributional knowledge. A particular attention is payed to ensuring its consistency. We then design a reasoning procedure able to make use of the large scale knowledge base. We experiment both with a deduction-based NLU system and with an abductive reasoner. For evaluation, we use three different NLU tasks: recognizing textual entailment, semantic role labeling, and interpretation of noun dependencies.

Download or read book Knowledge augmented Methods for Natural Language Processing written by Meng Jiang and published by Springer Nature. This book was released on with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Natural Language Processing and Knowledge Representation written by Łucja M. Iwańska and published by AAAI Press. This book was released on 2000-06-19 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.

Download or read book Natural Language Processing written by Ela Kumar and published by I. K. International Pvt Ltd. This book was released on 2013-12-30 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers all aspects of the area of linguistic analysis and the computational systems that have been developed to perform the language analysis. The book is primarily meant for post graduate and undergraduate technical courses.

Download or read book Natural Language Understanding written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-07-05 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Natural Language Understanding The field of artificial intelligence known as natural-language processing includes a subfield known as natural-language understanding (NLU), often known as natural-language interpretation (NLI), which deals with the reading comprehension of machines. Understanding natural language is seen as a challenging topic for artificial intelligence. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Natural Language Understanding Chapter 2: Computational Linguistics Chapter 3: Natural Language Processing Chapter 4: Parsing Chapter 5: Question Answering Chapter 6: Semantic Role Labeling Chapter 7: Computational Semantics Chapter 8: Semantic Parsing Chapter 9: Natural-language User Interface Chapter 10: History of Natural Language Processing (II) Answering the public top questions about natural language understanding. (III) Real world examples for the usage of natural language understanding in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of natural language understanding' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of natural language understanding.

Download or read book Representation Learning for Natural Language Processing written by Zhiyuan Liu and published by Springer Nature. This book was released on 2020-07-03 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Linguistics for the Age of AI written by Marjorie Mcshane and published by MIT Press. This book was released on 2021-03-02 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.

Download or read book Natural Language Processing NLP 2000 written by Dimitris N. Christodoulakis and published by Springer. This book was released on 2003-06-26 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers prepared for the 2nd International Conference on Natural Language Processing, held 2-4 June in Patras, Greece. The conference program features invited talks and submitted papers, c- ering a wide range of NLP areas: text segmentation, morphological analysis, lexical knowledge acquisition and representation, grammar formalism and s- tacticparsing,discourse analysis,languagegeneration,man-machineinteraction, machine translation, word sense disambiguation, and information extraction. The program committee received 71 abstracts, of which unfortunately no more than 50% could be accepted. Every paper was reviewed by at least two reviewers. The fairness of the reviewing process is demonstrated by the broad spread of institutions and countries represented in the accepted papers. So many have contributed to the success of the conference. The primary credit, ofcourse, goes to theauthors andto the invitedspeakers. By theirpapers and their inspired talks they established the quality of the conference. Secondly, thanks should go to the referees and to the program committee members who did a thorough and conscientious job. It was not easy to select the papers to be presented. Last, but not least, my special thanks to the organizing committee for making this conference happen.

Download or read book Natural Language Understanding written by James Allen and published by Pearson. This book was released on 1995 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a leading authority in artificial intelligence, this book delivers a synthesis of the major modern techniques and the most current research in natural language processing. The approach is unique in its coverage of semantic interpretation and discourse alongside the foundational material in syntactic processing.

Download or read book Computational Linguistics Speech And Image Processing For Arabic Language written by Neamat El Gayar and published by World Scientific. This book was released on 2018-09-18 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book encompasses a collection of topics covering recent advances that are important to the Arabic language in areas of natural language processing, speech and image analysis. This book presents state-of-the-art reviews and fundamentals as well as applications and recent innovations.The book chapters by top researchers present basic concepts and challenges for the Arabic language in linguistic processing, handwritten recognition, document analysis, text classification and speech processing. In addition, it reports on selected applications in sentiment analysis, annotation, text summarization, speech and font analysis, word recognition and spotting and question answering.Moreover, it highlights and introduces some novel applications in vital areas for the Arabic language. The book is therefore a useful resource for young researchers who are interested in the Arabic language and are still developing their fundamentals and skills in this area. It is also interesting for scientists who wish to keep track of the most recent research directions and advances in this area.

Download or read book The Age of Artificial Intelligence An Exploration written by Steven S. Gouveia and published by Vernon Press. This book was released on 2020-07-07 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: With worldwide spending estimates of over $97 billion by 2023, it is no surprise that Artificial Intelligence (A.I.) is one of the hottest topics at present in both the private and public spheres. Comprising of vital contributions from the most influential researchers in the field, including Daniel Dennett, Roman V. Yampolskiy, Frederic Gilbert, Stevan Harnad, David Pearce, Natasha Vita-More, Vernon Vinge and Ben Goertzel, ‘The Age of Artificial Intelligence: An Exploration’ discusses a variety of topics ranging from the various ethical issues associated with A.I. based technologies in terms of morality and law to subjects related to artificial consciousness, artistic creativity and intelligence. The volume is organized as follows: Section I is dedicated to reflections on the Intelligence of A.I., with chapters by Soenke Ziesche and Roman V. Yampolskiy, Stevan Harnad, Daniel Dennett and David Pearce. Next, Section II discusses the relationship between consciousness, simulation and artificial intelligence, with chapters by Gabriel Axel Montes and Ben Goertzel, Cody Turner, Nicole Hall and Steven S. Gouveia. Section III, dedicated to aesthetical creativity and language in artificial intelligence, includes chapters by Caterina Moruzzi, René Mogensen, Mariana Chinellato Ferreira and Kulvinder Panesar. The subsequent Section IV is on the Ethics of the Bionic Brain with the participation of Peter A. DePergola II, Tomislav Miletić and Frederic Gilbert, Aníbal M. Astobiza, Txetxu Ausin, Ricardo M. Ferrer and Stephen Rainey and Natasha Vita-More. Finally, Section V follows on the Ethics of Artificial Intelligence with chapters by Federico Pistono and Roman V. Yamploskiy, Hasse Hämäläinen, Vernon Vinge and Eray Özkural. The Age of Artificial Intelligence is imminent, if not here already. We should ensure that we invest in the right people and the right ideas to create the best possible solutions to the problems of the present and prepare for those of the future. This edited volume will be of particular interest to researchers in the field of A.I. as well of those in Cognitive Science (Philosophy of the Mind, Neuroscience, and Linguistics), Aesthetics and Arts, Applied Ethics and Political Philosophy / Law. Students studying the aforementioned topics can also benefit from its contents.

Download or read book Applied Natural Language Processing in the Enterprise written by Ankur A. Patel and published by "O'Reilly Media, Inc.". This book was released on 2021-05-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Linguistic Fundamentals for Natural Language Processing written by Emily M. Bender and published by Morgan & Claypool Publishers. This book was released on 2013-06-01 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages

Download or read book Natural Language Processing in Artificial Intelligence written by Brojo Kishore Mishra and published by CRC Press. This book was released on 2020-11-01 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Natural Language Processing with Python written by Steven Bird and published by "O'Reilly Media, Inc.". This book was released on 2009-06-12 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

Download or read book Information Retrieval in Biomedicine Natural Language Processing for Knowledge Integration written by Prince, Violaine and published by IGI Global. This book was released on 2009-03-31 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides relevant theoretical frameworks and the latest empirical research findings in biomedicine information retrieval as it pertains to linguistic granularity"--Provided by publisher.

Download or read book Introduction to Natural Language Processing written by Jacob Eisenstein and published by MIT Press. This book was released on 2019-10-01 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.