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Innovations In Nlp
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Book Synopsis Innovations in NLP by : L Michael Hall
Download or read book Innovations in NLP written by L Michael Hall and published by Crown House Publishing. This book was released on 2011-11-16 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: This long awaited book brings together some of the most recent innovations and applications of the traditional NLP model. Each chapter describes a new model or application and contains step by step instructions or a case study on how and when to apply it. For NLP Practitioners it provides an outstanding collection of new tools and ideas to take their practice forward.
Book Synopsis Advances in Intelligent Informatics, Smart Technology and Natural Language Processing by : Thanaruk Theeramunkong
Download or read book Advances in Intelligent Informatics, Smart Technology and Natural Language Processing written by Thanaruk Theeramunkong and published by Springer. This book was released on 2018-12-18 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th Joint International Symposium on Artificial Intelligence and Natural Language Processing, iSAI-NLP2017, held in Prachuap Khiri Khan, Thailand, in August 2017, and the 10th International Conference on Knowledge, Information and Creativity Support Systems, KICSS2015, held in Phuket, Thailand, in November 2015. It presents 22 carefully reviewed full papers on the following topics: artificial intelligence; machine learning; decision support systems; data mining; data analysis; natural language processing; multilingual processing; language and ontology unification; text classification; knowledge-based information systems; tracking systems; virtual reality; pattern recognition and image processing; signal classification; object detection and recognition; real-time sensor network; cloud-based services; and information security.
Book Synopsis Advances in Natural Language Processing by : Tapio Salakoski
Download or read book Advances in Natural Language Processing written by Tapio Salakoski and published by Springer. This book was released on 2006-08-11 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Conference on Natural Language Processing, FinTAL 2006, held in Turku, Finland in August 2006. The book presents 72 revised full papers together with 1 invited talk and the extended abstracts of 2 invited keynote addresses. The papers address all current issues in computational linguistics and monolingual and multilingual intelligent language processing - theory, methods and applications.
Book Synopsis Advances in Natural Language Processing by : Hrafn Loftsson
Download or read book Advances in Natural Language Processing written by Hrafn Loftsson and published by Springer. This book was released on 2010-08-11 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th International Conference on Advances in Natural Language Processing held in Reykjavik, Iceland, in August 2010.
Book Synopsis Natural Language Processing in Artificial Intelligence by : Brojo Kishore Mishra
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.
Book Synopsis Natural Language Processing In Healthcare by : Satya Ranjan Dash
Download or read book Natural Language Processing In Healthcare written by Satya Ranjan Dash and published by CRC Press. This book was released on 2022-09-13 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing In Healthcare: A Special Focus on Low Resource Languages covers the theoretical and practical aspects as well as ethical and social implications of NLP in healthcare. It showcases the latest research and developments contributing to the rising awareness and importance of maintaining linguistic diversity. The book goes on to present current advances and scenarios based on solutions in healthcare and low resource languages and identifies the major challenges and opportunities that will impact NLP in clinical practice and health studies.
Book Synopsis Advances in Natural Language Processing by : Hitoshi Isahara
Download or read book Advances in Natural Language Processing written by Hitoshi Isahara and published by Springer. This book was released on 2012-10-22 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Advances in Natural Language Processing, JapTAL 2012, Kanazawa, Japan, in October 2012. The 27 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 42 submissions. The papers are organized in topical sections on machine translation, multilingual issues, resouces, semantic analysis, sentiment analysis, as well as speech and generation.
Book Synopsis Handbook of Natural Language Processing and Machine Translation by : Joseph Olive
Download or read book Handbook of Natural Language Processing and Machine Translation written by Joseph Olive and published by Springer Science & Business Media. This book was released on 2011-03-02 with total page 956 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive handbook, written by leading experts in the field, details the groundbreaking research conducted under the breakthrough GALE program--The Global Autonomous Language Exploitation within the Defense Advanced Research Projects Agency (DARPA), while placing it in the context of previous research in the fields of natural language and signal processing, artificial intelligence and machine translation. The most fundamental contrast between GALE and its predecessor programs was its holistic integration of previously separate or sequential processes. In earlier language research programs, each of the individual processes was performed separately and sequentially: speech recognition, language recognition, transcription, translation, and content summarization. The GALE program employed a distinctly new approach by executing these processes simultaneously. Speech and language recognition algorithms now aid translation and transcription processes and vice versa. This combination of previously distinct processes has produced significant research and performance breakthroughs and has fundamentally changed the natural language processing and machine translation fields. This comprehensive handbook provides an exhaustive exploration into these latest technologies in natural language, speech and signal processing, and machine translation, providing researchers, practitioners and students with an authoritative reference on the topic.
Book Synopsis Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics by : Abhishek Kumar
Download or read book Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics written by Abhishek Kumar and published by CRC Press. This book was released on 2022-03-09 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges. This book is useful for research scholars and students involved in critical condition analysis and computation models.
Book Synopsis Natural Language Processing with SAS by :
Download or read book Natural Language Processing with SAS written by and published by . This book was released on 2020-08-31 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret, and emulate written or spoken human language. NLP draws from many disciplines including human-generated linguistic rules, machine learning, and deep learning to fill the gap between human communication and machine understanding. The papers included in this special collection demonstrate how NLP can be used to scale the human act of reading, organizing, and quantifying text data.
Book Synopsis Deep Learning for Natural Language Processing by : Stephan Raaijmakers
Download or read book Deep Learning for Natural Language Processing written by Stephan Raaijmakers and published by Simon and Schuster. This book was released on 2022-12-20 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the most challenging issues of natural language processing, and learn how to solve them with cutting-edge deep learning! Inside Deep Learning for Natural Language Processing you’ll find a wealth of NLP insights, including: An overview of NLP and deep learning One-hot text representations Word embeddings Models for textual similarity Sequential NLP Semantic role labeling Deep memory-based NLP Linguistic structure Hyperparameters for deep NLP Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. About the technology Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. About the book Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You’ll learn to use state-of the-art tools and techniques including BERT and XLNET, multitask learning, and deep memory-based NLP. Fascinating examples give you hands-on experience with a variety of real world NLP applications. Plus, the detailed code discussions show you exactly how to adapt each example to your own uses! What's inside Improve question answering with sequential NLP Boost performance with linguistic multitask learning Accurately interpret linguistic structure Master multiple word embedding techniques About the reader For readers with intermediate Python skills and a general knowledge of NLP. No experience with deep learning is required. About the author Stephan Raaijmakers is professor of Communicative AI at Leiden University and a senior scientist at The Netherlands Organization for Applied Scientific Research (TNO). Table of Contents PART 1 INTRODUCTION 1 Deep learning for NLP 2 Deep learning and language: The basics 3 Text embeddings PART 2 DEEP NLP 4 Textual similarity 5 Sequential NLP 6 Episodic memory for NLP PART 3 ADVANCED TOPICS 7 Attention 8 Multitask learning 9 Transformers 10 Applications of Transformers: Hands-on with BERT
Book Synopsis Practical Natural Language Processing by : Sowmya Vajjala
Download or read book Practical Natural Language Processing written by Sowmya Vajjala and published by O'Reilly Media. This book was released on 2020-06-17 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Representation Learning for Natural Language Processing by : Zhiyuan Liu
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.
Book Synopsis The Innovation Mode by : George Krasadakis
Download or read book The Innovation Mode written by George Krasadakis and published by Springer Nature. This book was released on 2020-07-29 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents unique insights and advice on defining and managing the innovation transformation journey. Using novel ideas, examples and best practices, it empowers management executives at all levels to drive cultural, technological and organizational changes toward innovation. Covering modern innovation techniques, tools, programs and strategies, it focuses on the role of the latest technologies (e.g., artificial intelligence to discover, handle and manage ideas), methodologies (including Agile Engineering and Rapid Prototyping) and combinations of these (like hackathons or gamification). At the same time, it highlights the importance of culture and provides suggestions on how to build it. In the era of AI and the unprecedented pace of technology evolution, companies need to become truly innovative in order to survive. The transformation toward an innovation-led company is difficult – it requires a strong leadership and culture, advanced technologies and well-designed programs. The book is based on the author’s long-term experience and novel ideas, and reflects two decades of startup, consulting and corporate leadership experience. It is intended for business, technology, and innovation leaders.
Book Synopsis Computing the Future: Exploring the Frontier of Intelligent Technologies by : Younes Keihani Far
Download or read book Computing the Future: Exploring the Frontier of Intelligent Technologies written by Younes Keihani Far and published by Nobel Sciences. This book was released on 2024-11-01 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapters Chapter 1: Transforming Natural Language Processing and Understanding Chapter 2: Unleashing the Power of Artificial Intelligence and Machine Learning Chapter 3: Networking and the Internet of Things: Building Secure and Connected Infrastructures Chapter 4: Information Technology: Enabling Digital Transformation Chapter 5: Unraveling the Potentials of Artificial Intelligent and Machine Learning to Diagnosis and treatment of Substance Use and Co-Occurring Mental Disorders Chapter 6: Redefining Hardware for AI: From Neuromorphic Chips to Quantum Computing
Book Synopsis Hands-On Natural Language Processing with Python by : Rajesh Arumugam
Download or read book Hands-On Natural Language Processing with Python written by Rajesh Arumugam and published by Packt Publishing Ltd. This book was released on 2018-07-18 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.
Book Synopsis Natural Language Processing for Social Media by : Atefeh Farzindar
Download or read book Natural Language Processing for Social Media written by Atefeh Farzindar and published by Morgan & Claypool Publishers. This book was released on 2017-12-15 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, healthcare, business intelligence, industry, marketing, and security and defence. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, virtual reality, and social networking. In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.
