Understanding Natural Language Understanding
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Understanding Natural Language Understanding
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Author : Erik Cambria
language : en
Publisher: Springer Nature
Release Date : 2024-10-22
Understanding Natural Language Understanding written by Erik Cambria and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-22 with Computers categories.
About half a century ago, AI pioneers like Marvin Minsky embarked on the ambitious project of emulating how the human mind encodes and decodes meaning. While today we have a better understanding of the brain thanks to neuroscience, we are still far from unlocking the secrets of the mind, especially when it comes to language, the prime example of human intelligence. “Understanding natural language understanding”, i.e., understanding how the mind encodes and decodes meaning through language, is a significant milestone in our journey towards creating machines that genuinely comprehend human language. Large language models (LLMs) such as GPT-4 have astounded us with their ability to generate coherent, contextually relevant text, seemingly bridging the gap between human and machine communication. Yet, despite their impressive capabilities, these models operate on statistical patterns rather than true comprehension. This textbook delves into the nuanced differences between these two paradigms and explores the future of AI as we strive to achieve true natural language understanding (NLU). LLMs excel at identifying and replicating patterns within vast datasets, producing responses that appear intelligent and meaningful. They can generate text that mimics human writing styles, provide summaries of complex documents, and even engage in extended dialogues with users. However, their limitations become evident when they encounter tasks that require deeper understanding, reasoning, and contextual knowledge. An NLU system that deconstructs meaning leveraging linguistics and semiotics (on top of statistical analysis) represents a more profound level of language comprehension. It involves understanding context in a manner similar to human cognition, discerning subtle meanings, implications, and nuances that current LLMs might miss or misinterpret. NLU grasps the semantics behind words and sentences, comprehending synonyms, metaphors, idioms, and abstract concepts with precision. This textbook explores the current state of LLMs, their capabilities and limitations, and contrasts them with the aspirational goals of NLU. The author delves into the technical foundations required for achieving true NLU, including advanced knowledge representation, hybrid AI systems, and neurosymbolic integration, while also examining the ethical implications and societal impacts of developing AI systems that genuinely understand human language. Containing exercises, a final assignment and a comprehensive quiz, the textbook is meant as a reference for courses on information retrieval, AI, NLP, data analytics, data mining and more.
Natural Language Understanding With Python
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Author : Deborah A. Dahl
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-06-30
Natural Language Understanding With Python written by Deborah A. Dahl and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Computers categories.
Build advanced NLU systems by utilizing NLP libraries such as NLTK, SpaCy, BERT, and OpenAI; ML libraries like Keras, scikit-learn, pandas, TensorFlow, and NumPy, along with visualization libraries such as Matplotlib and Seaborn. Purchase of the print Kindle book includes a free PDF eBook Key Features Master NLU concepts from basic text processing to advanced deep learning techniques Explore practical NLU applications like chatbots, sentiment analysis, and language translation Gain a deeper understanding of large language models like ChatGPT Book DescriptionNatural Language Understanding facilitates the organization and structuring of language allowing computer systems to effectively process textual information for various practical applications. Natural Language Understanding with Python will help you explore practical techniques for harnessing NLU to create diverse applications. with step-by-step explanations of essential concepts and practical examples, you’ll begin by learning about NLU and its applications. You’ll then explore a wide range of current NLU techniques and their most appropriate use-case. In the process, you’ll be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, you’ll also discover practical issues such as acquiring data, evaluating systems, and deploying NLU applications along with their solutions. The book is a comprehensive guide that’ll help you explore techniques and resources that can be used for different applications in the future. By the end of this book, you’ll be well-versed with the concepts of natural language understanding, deep learning, and large language models (LLMs) for building various AI-based applications.What you will learn Explore the uses and applications of different NLP techniques Understand practical data acquisition and system evaluation workflows Build cutting-edge and practical NLP applications to solve problems Master NLP development from selecting an application to deployment Optimize NLP application maintenance after deployment Build a strong foundation in neural networks and deep learning for NLU Who this book is for This book is for python developers, computational linguists, linguists, data scientists, NLP developers, conversational AI developers, and students looking to learn about natural language understanding (NLU) and applying natural language processing (NLP) technology to real problems. Anyone interested in addressing natural language problems will find this book useful. Working knowledge in Python is a must.
Understanding Natural Language
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Author : Terry Winograd
language : en
Publisher:
Release Date : 1972
Understanding Natural Language written by Terry Winograd and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972 with Computers categories.
Overview of the language understanding program; Comparison with previous programs; A grammar for english; An introduction to lisp; A description of programmar; Deduction, problem solving, and planner; The blocks world; Semantics; Refenreces; Appendices.
Natural Language Understanding
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Author : Kai Turing
language : en
Publisher: Publifye AS
Release Date : 2025-02-18
Natural Language Understanding written by Kai Turing and has been published by Publifye AS this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-18 with Computers categories.
""Natural Language Understanding"" explores how AI systems are increasingly able to interpret and respond to human language. It examines core principles like contextual modeling, where AI grasps meaning from surrounding text, and semantic interpretation, which extracts deeper meaning beyond simple keyword recognition. The book traces the evolution of Natural Language Understanding (NLU) from rule-based systems to modern deep learning approaches, highlighting the revolutionary impact of transformer networks. The book argues that recent advances, especially in transformer networks, signify a shift towards genuine comprehension rather than mere text processing. The book presents a comprehensive overview of NLU, beginning with the basics of linguistics and machine learning, then moving into contextual modeling and transformer architectures. Case studies and empirical results are used to support the arguments. The book progresses from fundamental concepts to advanced techniques and practical applications. It emphasizes real-world implementation, offering insights into how NLU can be applied across various industries. By addressing ethical considerations and future directions, ""Natural Language Understanding"" provides a valuable resource for anyone seeking to understand how machines can truly comprehend human language.
Natural Language Understanding In Conversational Ai With Deep Learning
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Author : Soyeon Caren Han
language : en
Publisher: Springer Nature
Release Date : 2025-01-11
Natural Language Understanding In Conversational Ai With Deep Learning written by Soyeon Caren Han and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-11 with Computers categories.
This book provides a comprehensive introduction to conversational spoken language understanding and surveys recent advances in conversational AI. It guides the reader through the history, current advancements, and future of natural language understanding (NLU) in human-computer interactions. To this end, the book is structured in seven chapters: Introduction to Natural Language Understanding lays the foundation by tracing the evolution of NLU from early human communication to modern human-computer interactions. Prerequisites and Glossary for Natural Language Understanding then serves as a foundational resource, consolidating essential prerequisites and key terminologies relevant across the book. Single-Turn Natural Language Understanding looks at Single-Turn NLU, focusing on tasks that involve interpreting and processing user inputs in a single interaction, while Multi-Turn Natural Language Understanding moves on systems for extended interactions with users and explores techniques for managing dialogues, using context and integrating external knowledge bases. Next, Evaluating Natural Language Understanding discusses the annotation of datasets and various performance assessment methods, covering different levels of understanding from intent recognition to slot filling and domain classification. Applications and Case Studies in Natural Language Understanding subsequently shows real-world applications of NLU in finance, medicine, and law. Eventually Challenges, Conclusions and Future Directions explores the core obstacles hindering the advancement of NLU, including ambiguity, domain adaptation, data scarcity, and ethical concerns. By understanding these challenges, this chapter highlights the ongoing work needed to advance NLU. This book mainly targets researchers, PhD students, and professionals who are entering this field and look for a state-of-the-art introduction to NLU applied in conversational systems such as chatbots, large language models, or educational systems.
Natural Language Understanding And Cognitive Robotics
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Author : Masao Yokota
language : en
Publisher: CRC Press
Release Date : 2019-12-06
Natural Language Understanding And Cognitive Robotics written by Masao Yokota and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-06 with Technology & Engineering categories.
In the not so distant future, we can expect a world where humans and robots coexist and interact with each other. For this to occur, we need to understand human traits, such as seeing, hearing, thinking, speaking, etc., and institute these traits in robots. The most essential feature necessary for robots to achieve is that of integrative multimedia understanding (IMU) which occurs naturally in humans. It allows us to assimilate pieces of information expressed through different modes such as speech, pictures, gestures, etc. The book describes how robots acquire traits like natural language understanding (NLU) as the central part of IMU. Mental image directed semantic theory (MIDST) is its core, and is based on the hypothesis that NLU is essentially the processing of mental image associated with natural language expressions, namely, mental-image based understanding (MBU). MIDST is intended to model omnisensory mental image in human and to afford a knowledge representation system in order for integrative management of knowledge subjective to cognitive mechanisms of intelligent entities such as humans and robots based on a mental image model visualized as ‘Loci in Attribute Spaces’ and its description language Lmd (mental image description language) to be employed for predicate logic with a systematic scheme for symbol-grounding. This language works as an interlingua among various kinds of information media, and has been applied to several versions of the intelligent system interlingual understanding model aiming at general system (IMAGES). Its latest version, i.e. conversation management system (CMS) simulates MBU and comprehends the user’s intention through dialogue to find and solve problems, and finally, provides a response in text or animation. The book is aimed at researchers and students interested in artificial intelligence, robotics, and cognitive science. Based on philosophical considerations, the methodology will also have an appeal in linguistics, psychology, ontology, geography, and cartography. Key Features: Describes the methodology to provide robots with human-like capability of natural language understanding (NLU) as the central part of IMU Uses methodology that also relates to linguistics, psychology, ontology, geography, and cartography Examines current trends in machine translation
Building Cognitive Applications With Ibm Watson Services Volume 7 Natural Language Understanding
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Author : Sebastian Vergara
language : en
Publisher: IBM Redbooks
Release Date : 2017-06-02
Building Cognitive Applications With Ibm Watson Services Volume 7 Natural Language Understanding written by Sebastian Vergara and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-02 with Computers categories.
The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® WatsonTM cognitive computing services. The series includes an overview of specific IBM Watson® services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases. The series includes the following volumes: Volume 1 Getting Started, SG24-8387 Volume 2 Conversation, SG24-8394 Volume 3 Visual Recognition, SG24-8393 Volume 4 Natural Language Classifier, SG24-8391 Volume 5 Language Translator, SG24-8392 Volume 6 Speech to Text and Text to Speech, SG24-8388 Volume 7 Natural Language Understanding, SG24-8398 Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool. This IBM Redbooks® publication, Volume 7, introduces the Watson Natural Language Understanding service. This service is a collection of text analysis functions that derive semantic information from your content. This book includes a basic description of several of the Natural Language Understanding service features and provides sample code snippets to demonstrate their use. This book includes an example of an application that integrates the Watson Natural Language Understanding service with the Watson Personality Insights and Insights for Twitter services to create a simple application to analyze Tweets from a Twitter handle. You can develop and deploy the sample applications by following along in a step-by-step approach and using provided code snippets. Alternatively, you can download an existing Git project to more quickly deploy the application.
Natural Language Understanding
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2023-07-05
Natural Language Understanding written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-05 with Computers categories.
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.
Machine Learning And Deep Learning In Natural Language Processing
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Author : Anitha S. Pillai
language : en
Publisher: CRC Press
Release Date : 2023-10-18
Machine Learning And Deep Learning In Natural Language Processing written by Anitha S. Pillai and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-18 with Computers categories.
Natural Language Processing (NLP) is a sub-field of Artificial Intelligence, linguistics, and computer science and is concerned with the generation, recognition, and understanding of human languages, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then they utilize algorithms to extract meaning and produce results. Machine Learning and Deep Learning in Natural Language Processing aims at providing a review of current Neural Network techniques in the NLP field, in particular about Conversational Agents (chatbots), Text-to-Speech, management of non-literal content – like emotions, but also satirical expressions – and applications in the healthcare field. NLP has the potential to be a disruptive technology in various healthcare fields, but so far little attention has been devoted to that goal. This book aims at providing some examples of NLP techniques that can, for example, restore speech, detect Parkinson’s disease, or help psychotherapists. This book is intended for a wide audience. Beginners will find useful chapters providing a general introduction to NLP techniques, while experienced professionals will appreciate the chapters about advanced management of emotion, empathy, and non-literal content.
The Development Of Natural Language Processing
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Author : China Info & Comm Tech Grp Corp
language : en
Publisher: Springer Nature
Release Date : 2021-06-09
The Development Of Natural Language Processing written by China Info & Comm Tech Grp Corp and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-09 with Computers categories.
This book is a part of the Blue Book series “Research on the Development of Electronic Information Engineering Technology in China”, which explores the cutting edge of natural language processing (NLP) studies. The research objects of natural language processing are evolved from words, phrases, and sentences to text, and research directions are from language analysis, language understanding, language generation, knowledge graphs, machine translation, to deep semantic understanding, and beyond. This is in line with the development trend of applications. And for another typical NLP application machine translation, from text translation, to voice and image translation, now simultaneous interpretation, progress of technology makes the application of machine translation deeper and wider into diverse industries. This book is intended for researchers and industrial staffs who have been following the current situation and future trends of the natural language processing. Meanwhile, it also bears high value of reference for experts, scholars, and technical and engineering managers of different levels and different fields.