Future and Emerging Trends in Language Technology Machine Learning and Big Data

This book constitutes revised selected papers from the Second International Workshop on Future and Emerging Trends in Language Technology, FETLT 2016, which took place in Seville, Spain, in November 2016.

Future and Emerging Trends in Language Technology  Machine Learning and Big Data

This book constitutes revised selected papers from the Second International Workshop on Future and Emerging Trends in Language Technology, FETLT 2016, which took place in Seville, Spain, in November 2016. The 10 full papers and 5 position papers presented in this volume were carefully reviewed and selected from 18 submissions. In 2016 the conference focused on Machine Learning and Big Data.

Digital Teaching and Learning Perspectives for English Language Education

Chatbots/Virtual Tutors Chatbots are AI systems that imitate discursive behaviours of humans. ... Big-Data-Analysis AI-tools nowadays have access to a large amount of data. ... Future and Emerging Trends in Language Technology. Machine ...

Digital Teaching and Learning  Perspectives for English Language Education

The ongoing digitalization of social environments and personal lifeworlds has made it crucial to pinpoint the possibilities of digital teaching and learning also in the context of English language education. This book offers university students, trainee teachers, in-service teachers and teacher educators an in-depth exploration of the intricate relationship between English language education and digital teaching and learning. Located at the intersection of research, theory and teaching practice, it thoroughly legitimizes the use of digital media in English language education and provides concrete scenarios for their competence-oriented and task-based classroom use.

Data Science and Digital Business

IEEE Transactions on Speech and Audio Processing,8(1), 11–23. 13. McTear, M. F. (2017). Future and emerging trends in language technology. In Second International Workshop on Machine Learning and Big Data, FETLT 2016, Chap.

Data Science and Digital Business

This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.

Conversational Dialogue Systems for the Next Decade

McTear MF (2016) The rise of the conversational interface: a new kid on the block? In: Proceedings of the second international workshop future and emerging trends in language technology. Machine learning and big data (FETLT), Seville, ...

Conversational Dialogue Systems for the Next Decade

This book compiles and presents a synopsis on current global research efforts to push forward the state of the art in dialogue technologies, including advances to the classical problems of dialogue management, language generation, question answering, human–robot interaction, chatbots design and evaluation, as well as topics related to the human nature of the conversational phenomena such as humour, social context, specific applications for e-health, understanding, and awareness

AI for Marketing and Product Innovation

Reading this book is the first step to getting there." —Stef Strack, CEO Rag & Bone, New York "Now brands and retailers can think like a customer versus just thinking about the customer AI for Marketing and Product Innovation arms leaders ...

AI for Marketing and Product Innovation

Get on board the next massive marketing revolution AI for Marketing and Product Innovation offers creatives and marketing professionals a non-tech guide to artificial intelligence (AI) and machine learning (ML)—twin technologies that stand poised to revolutionize the way we sell. The future is here, and we are in the thick of it; AI and ML are already in our lives every day, whether we know it or not. The technology continues to evolve and grow, but the capabilities that make these tools world-changing for marketers are already here—whether we use them or not. This book helps you lean into the curve and take advantage of AI’s unparalleled and rapidly expanding power. More than a simple primer on the technology, this book goes beyond the “what” to show you the “how”: How do we use AI and ML in ways that speak to the human spirit? How to we translate cold technological innovation into creative tools that forge deep human connections? Written by a team of experts at the intersection of neuroscience, technology, and marketing, this book shows you the ins and outs of these groundbreaking technological tools. Understand AI and ML technology in layman’s terms Harness the twin technologies unparalleled power to transform marketing Learn which skills and resources you need to use AI and ML effectively Employ AI and ML in ways that resonate meaningfully with customers Learn practical examples of how to reinvest product innovation, brand building, targeted marketing and media measurement to connect with people and enhance ROI Discover the true impact of AI and ML from real-world examples, and learn the thinking, best practices, and metrics you need to capture this lightning and take the next massive leap in the evolution of customer connection. AI for Marketing and Product Innovation shows you everything you need to know to get on board.

Shaping the Future of ICT

Computer Modelling & New Technologies 18(12A): 147–151. Liu, Y., J. Yang, Y. Huang, L. Xu, S. Li, and M. Qi. 2015. MapReduce based parallel neural networks in enabling large scale machine learning. Computational Intelligence and ...

Shaping the Future of ICT

The International Conference on Communications, Management, and Information Technology (ICCMIT’16) provides a discussion forum for scientists, engineers, educators and students about the latest discoveries and realizations in the foundations, theory, models and applications of systems inspired on nature, using computational intelligence methodologies, as well as in emerging areas related to the three tracks of the conference: Communication Engineering, Knowledge, and Information Technology. The best 25 papers to be included in the book will be carefully reviewed and selected from numerous submissions, then revised and expanded to provide deeper insight into trends shaping future ICT.

Tech Trends in Practice

In this book, best-selling author, strategic business advisor, and respected futurist Bernard Marr explains the role of technology in providing innovative businesses solutions for companies of varying sizes and across different industries.

Tech Trends in Practice

Discover how 25 powerful technology trends are transforming 21st century businesses How will the latest technologies transform your business? Future Tech Trends in Practice will give you the knowledge of today’s most important technology trends, and how to take full advantage of them to grow your business. The book presents25 real-world technology trends along with their potential contributions to organisational success. You’ll learn how to integrate existing advancements and plan for those that are on the way. In this book, best-selling author, strategic business advisor, and respected futurist Bernard Marr explains the role of technology in providing innovative businesses solutions for companies of varying sizes and across different industries. He covers wide-ranging trends and provides an overview of how companies are using these new and emerging technologies in practice. You, too, can prepare your company for the potential and power of trending technology by examining these and other areas of innovation described in Future Tech Trends in Practice: Artificial intelligence, including machine and deep learning The Internet of Things and the rise of smart devices Self-driving cars and autonomous drones 3D printing and additive manufacturing Blockchain technology Genomics and gene editing Augmented, virtual and mixed reality When you understand the technology trends that are driving success, now and into the future, you’ll be better positioned to address and solve problems within your organisation.

Advanced Deep Learning Applications in Big Data Analytics

From this, we can say that our future work list may contain the following actions: • Accuracy calculation and performance evaluation: In ... International Journal of Emerging Trends & Technology in Computer Science, 3(4), 313–320.

Advanced Deep Learning Applications in Big Data Analytics

Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.

Proceedings of the 2nd International Conference on Recent Trends in Machine Learning IoT Smart Cities and Applications

Common AI techniques in which machine learning procedures are used for structured data are neural network and the classical support vector machine in addition to NLP (natural language processing) and modern deep learning is for data ...

Proceedings of the 2nd International Conference on Recent Trends in Machine Learning  IoT  Smart Cities and Applications


Smart Technologies

Big data analytics deals with the discovery, interpretation and the subsequent communication of insightful patterns ... are harnessing the power of analytics to forecast their growth, emerging trends and future business opportunities.

Smart Technologies

The book introduces the concept of ‘smart technologies’, especially ‘Internet of Things’ (IoT), and elaborates upon various constituent technologies, their evolution and their applications to various challenging problems in society. It then presents research papers and case studies based upon inception, application and implementation of IoT-based smart technologies for various application areas from some of the most technologically conservative domains like agriculture and farming to the most advanced areas such as automobiles, financial transactions and industrial applications. The book contents is thus applicable not only to academic researcher, but also to interested readers from industries and corporates, and those involved in policy making. Excerpt from the Foreword (read the complete text on Springerlink): “This book contains besides the two introductory chapters, written by the project leaders from Indian Institute of Science (IISc) Bangalore, and TU Clausthal (TUC), Germany, the different areas of research work done within the INGPAR (Indo-German Partnership in Advanced Research, founded by DAAD in Germany and UGC in India) project so far by the Indian and German young researchers. It offers new perspectives and documents important progress in smart technologies. I can say without reservation that this book and, more specifically, the method it espouses will change fundamental ideas for cutting-edge innovation and disruption in the smart technology area.” - Prof. Dr. Thomas Hanschke, President, TU Clausthal, Clausthal-Zellerfeld, Germany

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020.

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Measuring the Digital Transformation A Roadmap for the Future

1.1 Technology trends AI technologies AI-related inventions have accelerated since 2010 and continue to grow at a much ... ML and other AI-related developments, coupled with technologies such as Big data analytics and cloud computing, ...

Measuring the Digital Transformation A Roadmap for the Future

Measuring the Digital Transformation: A Roadmap for the Future provides new insights into the state of the digital transformation by mapping indicators across a range of areas – from education and innovation, to trade and economic and social outcomes – against current digital policy issues, as presented in Going Digital: Shaping Policies, Improving Lives.

Big Data Technologies and Applications

McKenzie M, Wong S. Subset selection of training data for machine learning: a situational awareness system case study. ... Report: Data Visualization Applications Market Future Of Decision Making Trends, Forecasts And The Challengers ...

Big Data Technologies and Applications

The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.

ARTIFICIAL INTELLIGENCE

It is aimed at getting broader views of the current trends with AI. A spectrum of opportunities lies open for all with AI and current technologies. Big data and cloud are the next things discussed here; AI has its impact and need ...

ARTIFICIAL INTELLIGENCE

There has been a movement over the years to make machines intelligent. With the advent of modern technology, AI has become the core part of day-to-day life. But it is accentuated to have a book that keeps abreast of all the state-of-the-art concepts (pertaining to AI) in simplified, explicit and elegant way, expounding on ample examples so that the beginners are able to comprehend the subject with ease. The book on Artificial Intelligence, dexterously divided into 21 chapters, fully satisfies all these pressing needs. It is intended to put each and every concept related to intelligent system in front of the readers in the most simplified way so that while understanding the basic concepts, they will develop thought process that can contribute to the building of advanced intelligent systems. Various cardinal landmarks pertaining to the subject such as problem solving, search techniques, intelligent agents, constraint satisfaction problems, knowledge representation, planning, machine learning, natural language processing, pattern recognition, game playing, hybrid and fuzzy systems, neural network-based learning and future work and trends in AI are now under the single umbrella of this book, thereby showing a nice blend of theoretical and practical aspects. With all the latest information incorporated and several pedagogical attributes included, this textbook is an invaluable learning tool for the undergraduate and postgraduate students of computer science and engineering, and information technology. KEY FEATURES • Highlights a clear and concise presentation through adequate study material • Follows a systematic approach to explicate fundamentals as well as recent advances in the area • Presents ample relevant problems in the form of multiple choice questions, concept review questions, critical thinking exercise and project work • Incorporates various case studies for major topics as well as numerous industrial examples

The Future of Artificial Intelligence in Digital Marketing

Current systems offer little to no support for such Big Data pipelines and this is in itself a challenging ... 2.4 Big data Technologies Big data contains of techniques for analyzing data , such as A / B testing , machine learning and ...

The Future of Artificial Intelligence in Digital Marketing

Not long ago, Artificial Intelligence (AI) only existed in the realm of science fiction. Today, it’s a reality and is only growing more prominent each day, spreading across both every imaginable industry and countries around the world. But what is the number one AI modern person interacting with on a daily basis? The Internet. While search engine technology has been around for a few years, page-rank algorithms have been revolutionized by the introduction of AI technologies. Because this trend will continue into the foreseeable future, and become increasingly more important as the years go on, any digital marketer, small business owner, or social media user needs to know how it all works—and how you can use it to your advantage. In The Future of Artificial Intelligence in Digital Marketing, you will dive into the details of artificial intelligence (AI) and how it has dramatically affected digital marketing. Documenting the advancement of AI digital marketing, The Future of Artificial Intelligence in Digital Marketing offers proven solutions to mastering digital processes and search engines. The importance of applying empathic machines in digital marketing can’t be overstated—nor can the benefits of using humanized AI digital marketing. Revolutionize your digital marketing world with The Future of Artificial Intelligence in Digital Marketing.

Handbook of Research on Emerging Trends and Applications of Machine Learning

Next, the ethical discussions surrounding the autonomous vehicle involving stakeholders, technologies, social environments, and costs vs. quality ... Chapter 24 Sentiment Analysis on Social Media: Recent Trends in Machine Learning .

Handbook of Research on Emerging Trends and Applications of Machine Learning

As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.

Trends in Deep Learning Methodologies

Precisely for this reason, the combination of machine learning and big data is extremely useful in bringing ... in the field of artificial intelligence in recent years, having as its main engine deep learning-based technologies, ...

Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

The Emerging Technology of Big Data

Understanding how big data works is by understanding how to use data science. ... making prediction, or future trends, and it is the key that applies technology to various fieldwork like healthcare, science, engineering, business, ...

The Emerging Technology of Big Data

Big Data is now highly regarded and accepted as a useful tool to help organizations manage their data and information effectively and efficiently. This new volume, The Emerging Technology of Big Data: Its Impact as a Tool for ICT Development, looks at the new technology that has emerged to meet the growing need and demand and studies the impact of Big Data in several areas of today’s society, including social media, business process re-engineering, science, e-learning, higher education, business intelligence, and green computing. In today’s modern society, information system (IS) through Big Data contributes to the success of organizations because it provides a solid foundation for increasing both efficiency and productivity. Many business organizations and educational institutions realize that compliance with Big Data will affect their prospects for success. Everyday, the amount of data collected from digital tools grows tremendously. As the amount of data increases, the use of IS becomes more and more essential. The book looks at how large datasets and analytics have slowly crept into the world of education and discusses methods of teaching and learning and the collection of student-learning data. The final chapter of the book considers the environmental impacts of ICT and emphasizes green ICT awareness as a corporate strategy through information systems. The global ICT industry accounts for approximately 2 percent of global carbon dioxide (CO2) emissions, and the manufacture, shipping, and disposal of ICT equipment also contributes environmentally. This chapter addresses these issues. The information provided here will be valuable information for education professionals, businesses, faculty, scientists and researchers, and others.

An Introduction to Artificial Intelligence in Education

This book systematically reviews a broad range of cases in education that utilize cutting-edge AI technologies.

An Introduction to Artificial Intelligence in Education

This book systematically reviews a broad range of cases in education that utilize cutting-edge AI technologies. Furthermore, it introduces readers to the latest findings on the scope of AI in education, so as to inspire researchers from non-technological fields (e.g. education, psychology and neuroscience) to solve education problems using the latest AI techniques. It also showcases a number of established AI systems and products that have been employed for education. Lastly, the book discusses how AI can offer an enabling technology for critical aspects of education, typically including the learner, content, strategy, tools and environment, and what breakthroughs and advances the future holds. The book provides an essential resource for researchers, students and industrial practitioners interested and engaged in the fields of AI and education. It also offers a convenient handbook for non-professional readers who need a primer on AI in education, and who want to gain a deeper understanding of emerging trends in this domain.

Proceedings of the International Conference on Big Data IoT and Machine Learning

In the future, we would like to run different disease's dataset for early disease prediction in our model. ... In: 2018 international joint symposium on artificial intelligence and natural language processing (Isai-NLP).

Proceedings of the International Conference on Big Data  IoT  and Machine Learning