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Innovations in NLP by L Michael Hall,Shelle Rose Charvet Pdf
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.
Natural Language Processing In Healthcare by Satya Ranjan Dash,Shantipriya Parida,Esaú Villatoro Tello,Biswaranjan Acharya,Ondřej Bojar Pdf
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.
Natural Language Processing with SAS by Anonim Pdf
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.
Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics by Abhishek Kumar,Ashutosh Kumar Dubey,Sreenatha G. Anavatti,Pramod Singh Rathore Pdf
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.
Natural Language Processing in Artificial Intelligence by Brojo Kishore Mishra,Raghvendra Kumar Pdf
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.
Representation Learning for Natural Language Processing by Zhiyuan Liu,Yankai Lin,Maosong Sun Pdf
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.
Natural Language Processing for Social Media by Atefeh Farzindar,Diana Inkpen Pdf
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.
Handbook of Natural Language Processing and Machine Translation by Joseph Olive,Caitlin Christianson,John McCary Pdf
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.
Innovative Instructional Design Methods and Tools for Improved Teaching by Khaldi, Mohamed Pdf
In the complex field of academic scholarship, educators and scholars often encounter the challenge of designing effective learning scenarios that align with various educational objectives. The process involves meticulous planning, consideration of diverse pedagogical approaches, and adapting strategies to different circumstances and situations. The need for innovative solutions in pedagogy has never been more pressing, with topics ranging from instructional design to emerging techno pedagogical practices demanding attention. Academic scholars are yearning for a comprehensive guide that not only dissects the intricacies of these challenges but also offers transformative solutions to navigate the evolving landscape of education. Innovative Instructional Design Methods and Tools for Improved Teaching is a groundbreaking book meticulously crafted to address the pressing issues faced by academic scholars today. This book transcends the conventional boundaries of educational discourse, offering a roadmap for designing learning activities beyond routine exercises. It unveils a comprehensive approach, integrating pedagogical strategies and innovative teaching practices, providing educators with the tools they need to revolutionize their approach to instruction. This book is a solution to the challenges educators face in the contemporary academic landscape, providing a transformative guide for those seeking to excel in the dynamic field of pedagogy.
This fully revised edition brings you a brilliant Richard Bandler master training and significant contributions from Eric Robbie, Wyatt Woodsmall, Tad James, Christina Hall and the late Will MacDonald. "No other book covers this breadth of NLP Master Practitioner material." Frank Daniels, NLP trainer
Quality Innovation: Knowledge, Theory, and Practices by Al-Hakim, Latif Pdf
Internet and social networks play a critical role in the evolution of processes and functional areas that allow businesses to reach a wider base of end-users and achieve competitive advantage in their respective markets. Quality Innovation: Knowledge, Theory, and Practices presents a compilation of recent theoretical frameworks, case studies, and empirical research findings in the area of quality innovation. It highlights the theories, strategies, and potential concerns for organizations engaged in change management designed to address stakeholders needs. This reference volume serves as a valuable resource for researchers, business professionals, and students in a variety of fields and disciplines.
Thorsons Way of NLP by Joseph O'Connor,Ian McDermott Pdf
NLP, Neuro-Linguistic Programming, is one of the fastest-growing developments in applied psychology. This clear and accessible guide, for both the practitioner and the layman, explains what NLP is and how to use personally, spiritually and professionally. 5 line drawings.
Innovations and Applications of Technology in Language Education by Hung Phu Bui,Raghvendra Kumar,Nilayam Kumar Kamila Pdf
The linguistics and language education world has recently experienced a rapidly proliferating interest in applying technology. This interdisciplinary area bridges the gap between two previously separate fields. Innovations and Applications of Technology in Language Education is a collection of 12 chapters by an international group of language and linguistics education experts. Although technology in language education is a global interest, its practices should be contextualized. This book covers how language educational technology is currently applied, discusses how it should be applied, and gives directions for its future development. Providing a critical review of respective current practices and perspectives, this book begins by presenting a set of research‐based principles for developing second language teachers’ professionalism. It then examines the use of technology to enhance students’ English language skills. Acknowledging the advantages and disadvantages of AI‐mediated communication, this book argues for the use of AI to facilitate communication in language education. It also proposes the use of AI to develop and administer language tests and suggests guidelines for practitioners to deploy AI in developing and administering language tests efficiently. This book concludes by discussing technology for specific purposes in second language education and the potential of computer‐mediated communication (CMC) to enhance interaction between students.
Practical Natural Language Processing by Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana Pdf
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
Hands-On Natural Language Processing with Python by Rajesh Arumugam,Rajalingappaa Shanmugamani Pdf
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.