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Big Data, Cloud and Applications: Third International Conference, BDCA 2018, Kenitra, Morocco, April 4–5, 2018, Revised Selected Papers (Communications in Computer and Information Science #872)
by Youness Tabii Mohamed Lazaar Mohammed Al Achhab Nourddine EnneyaThis book constitutes the thoroughly refereed proceedings of the Third International Conference on Big Data, Cloud and Applications, BDCA 2018, held in Kenitra, Morocco, in April 2018.The 45 revised full papers presented in this book were carefully selected from 99 submissions with a thorough double-blind review process. They focus on the following topics: big data, cloud computing, machine learning, deep learning, data analysis, neural networks, information system and social media, image processing and applications, and natural language processing.
Big Data, Cloud Computing, and Data Science Engineering (Studies in Computational Intelligence #844)
by Roger LeeThis edited book presents the scientific outcomes of the 4th IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2019) which was held on May 29–31, 2019 in Honolulu, Hawaii. The aim of the conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Presenting 15 of the conference’s most promising papers, the book discusses all aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them.
Big Data, Cloud Computing, and Data Science Engineering (Studies in Computational Intelligence #1075)
by Roger LeeThis book presents scientific results of the 7th IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2021) which was held on August 4-6, 2022 in Danang, Vietnam. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. All aspects (theory, applications, and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here in the results of the articles featured in this book. The conference organizers selected the best papers from those papers accepted for presentation at the conference. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 15 of the conference’s most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.
Big Data, Cloud Computing and IoT: Tools and Applications
by Sita Rani Pankaj Bhambri Aman Kataria Alex Khang Arun Kumar SivaramanCloud computing, the Internet of Things (IoT), and big data are three significant technological trends affecting the world's largest corporations. This book discusses big data, cloud computing, and the IoT, with a focus on the benefits and implementation problems. In addition, it examines the many structures and applications pertinent to these disciplines. Also, big data, cloud computing, and the IoT are proposed as possible study avenues. Features: Informs about cloud computing, IoT and big data, including theoretical foundations and the most recent empirical findings Provides essential research on the relationship between various technologies and the aggregate influence they have on solving real-world problems Ideal for academicians, developers, researchers, computer scientists, practitioners, information technology professionals, students, scholars, and engineers exploring research on the incorporation of technological innovations to address contemporary societal challenges
Big Data, Cloud Computing and IoT: Tools and Applications
Cloud computing, the Internet of Things (IoT), and big data are three significant technological trends affecting the world's largest corporations. This book discusses big data, cloud computing, and the IoT, with a focus on the benefits and implementation problems. In addition, it examines the many structures and applications pertinent to these disciplines. Also, big data, cloud computing, and the IoT are proposed as possible study avenues. Features: Informs about cloud computing, IoT and big data, including theoretical foundations and the most recent empirical findings Provides essential research on the relationship between various technologies and the aggregate influence they have on solving real-world problems Ideal for academicians, developers, researchers, computer scientists, practitioners, information technology professionals, students, scholars, and engineers exploring research on the incorporation of technological innovations to address contemporary societal challenges
Big Data, Cloud Computing, Data Science & Engineering (Studies in Computational Intelligence #786)
by Roger LeeThis book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference’s most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science.
Big Data, Code and the Discrete City: Shaping Public Realms (Routledge Studies in Urbanism and the City)
by Silvio CartaBig Data, Code and the Discrete City explores how digital technologies are gradually changing the way in which the public space is designed by architects, managed by policymakers and experienced by individuals. Smart city technologies are superseding the traditional human experience that has characterised the making of the public space until today. This book examines how computers see the public space and the effect of algorithms, artificial intelligences and automated processes on the human experience in public spaces. Divided into three parts, the first part of this book examines the notion of discreteness in its origins and applications to computer sciences. The second section presents a dual perspective: it explores the ways in which public spaces are constructed by the computer-driven logic and then translated into control mechanisms, design strategies and software-aided design. This perspective also describes the way in which individuals perceive this new public space, through its digital logic, and discrete mechanisms (from Wi-Fi coverage to self-tracking). Finally, in the third part, this book scrutinises the discrete logic with which computers operate, and how this is permeating into aspects of city life. This book is valuable for anyone interested in urban studies and digital technologies, and more specifically in big data, urban informatics and public space.
Big Data, Code and the Discrete City: Shaping Public Realms (Routledge Studies in Urbanism and the City)
by Silvio CartaBig Data, Code and the Discrete City explores how digital technologies are gradually changing the way in which the public space is designed by architects, managed by policymakers and experienced by individuals. Smart city technologies are superseding the traditional human experience that has characterised the making of the public space until today. This book examines how computers see the public space and the effect of algorithms, artificial intelligences and automated processes on the human experience in public spaces. Divided into three parts, the first part of this book examines the notion of discreteness in its origins and applications to computer sciences. The second section presents a dual perspective: it explores the ways in which public spaces are constructed by the computer-driven logic and then translated into control mechanisms, design strategies and software-aided design. This perspective also describes the way in which individuals perceive this new public space, through its digital logic, and discrete mechanisms (from Wi-Fi coverage to self-tracking). Finally, in the third part, this book scrutinises the discrete logic with which computers operate, and how this is permeating into aspects of city life. This book is valuable for anyone interested in urban studies and digital technologies, and more specifically in big data, urban informatics and public space.
Big Data Computing: A Guide for Business and Technology Managers (Chapman & Hall/CRC Big Data Series)
by Vivek KaleThis book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It provides a framework that enables business and technical managers to make optimal decisions necessary for the successful migration to Big Data computing environments and applications within their organizations.
Big Data Computing: A Guide for Business and Technology Managers (Chapman & Hall/CRC Big Data Series)
by Vivek KaleThis book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It provides a framework that enables business and technical managers to make optimal decisions necessary for the successful migration to Big Data computing environments and applications within their organizations.
Big Data Computing: Advances in Technologies, Methodologies, and Applications (Computational Intelligence Techniques)
by Tanvir Habib Sardar Bishwajeet Kumar PandeyThis book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing.
Big Data Computing
Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix
Big Data Computing: Advances in Technologies, Methodologies, and Applications (Computational Intelligence Techniques)
This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing.
Big Data Computing and Communications: First International Conference, BigCom 2015, Taiyuan, China, August 1-3, 2015, Proceedings (Lecture Notes in Computer Science #9196)
by Yu Wang Hui Xiong Shlomo Argamon XiangYang Li JianZhong LiThis book constitutes the proceedings of the First International Conference on Big Data Computing and Communications, BigCom 2015, held in Taiyuan, China, in August 2015. The 41 papers presented in this volume were carefully reviewed and selected from 74 submissions. They were organized in topical sections named: wireless communication and networks; database and big data; smart phone and sensing application; security and privacy; architecture and applications; sensor networks and RFID; social networks and recommendation; signal processing and pattern recognition; and routing and resource management.
Big Data Computing and Communications: Second International Conference, BigCom 2016, Shenyang, China, July 29-31, 2016. Proceedings (Lecture Notes in Computer Science #9784)
by Yu Wang Ge Yu Yanyong Zhang Zhu Han Guoren WangThis book constitutes the proceedings of the Second International Conference on Big Data Computing and Communications, BigCom 2016, held in Shenyang, China, in July 2016. The 39 papers presented in this volume were carefully reviewed and selected from 90 submissions. BigCom is an international symposium dedicated to addressing the challenges emerging from big data related computing and networking. The conference is targeted to attract researchers and practitioners who are interested in Big Data analytics, management, security and privacy, communication and high performance computing in its broadest sense.
Big Data Concepts, Technologies, and Applications
by Mohammad Shahid Husain Mohammad Zunnun Khan Tamanna SiddiquiWith the advent of such advanced technologies as cloud computing, the Internet of Things, the Medical Internet of Things, the Industry Internet of Things and sensor networks as well as the exponential growth in the usage of Internet-based and social media platforms, there are enormous oceans of data. These huge volumes of data can be used for effective decision making and improved performance if analyzed properly. Due to its inherent characteristics, big data is very complex and cannot be handled and processed by traditional database management approaches. There is a need for sophisticated approaches, tools and technologies that can be used to store, manage and analyze these enormous amounts of data to make the best use of them. Big Data Concepts, Technologies, and Applications covers the concepts, technologies, and applications of big data analytics. Presenting the state-of-the-art technologies in use for big data analytics. it provides an in-depth discussion about the important sectors where big data analytics has proven to be very effective in improving performance and helping industries to remain competitive. This book provides insight into the novel areas of big data analytics and the research directions for the scholars working in the domain. Highlights include: The advantages, disadvantages and challenges of big data analytics State-of-the-art technologies for big data analytics such as Hadoop, NoSQL databases, data lakes, deep learning and blockchain The application of big data analytic in healthcare, business, social media analytics, fraud detection and prevention and governance Exploring the concepts and technologies behind big data analytics, the book is an ideal resource for researchers, students, data scientists, data analysts and business analysts who need insight into big data analytics
Big Data Concepts, Technologies, and Applications
by Mohammad Shahid Husain Mohammad Zunnun Khan Tamanna SiddiquiWith the advent of such advanced technologies as cloud computing, the Internet of Things, the Medical Internet of Things, the Industry Internet of Things and sensor networks as well as the exponential growth in the usage of Internet-based and social media platforms, there are enormous oceans of data. These huge volumes of data can be used for effective decision making and improved performance if analyzed properly. Due to its inherent characteristics, big data is very complex and cannot be handled and processed by traditional database management approaches. There is a need for sophisticated approaches, tools and technologies that can be used to store, manage and analyze these enormous amounts of data to make the best use of them. Big Data Concepts, Technologies, and Applications covers the concepts, technologies, and applications of big data analytics. Presenting the state-of-the-art technologies in use for big data analytics. it provides an in-depth discussion about the important sectors where big data analytics has proven to be very effective in improving performance and helping industries to remain competitive. This book provides insight into the novel areas of big data analytics and the research directions for the scholars working in the domain. Highlights include: The advantages, disadvantages and challenges of big data analytics State-of-the-art technologies for big data analytics such as Hadoop, NoSQL databases, data lakes, deep learning and blockchain The application of big data analytic in healthcare, business, social media analytics, fraud detection and prevention and governance Exploring the concepts and technologies behind big data analytics, the book is an ideal resource for researchers, students, data scientists, data analysts and business analysts who need insight into big data analytics
Big Data Concepts, Theories, and Applications
by Shui Yu Song GuoThis book covers three major parts of Big Data: concepts, theories and applications. Written by world-renowned leaders in Big Data, this book explores the problems, possible solutions and directions for Big Data in research and practice. It also focuses on high level concepts such as definitions of Big Data from different angles; surveys in research and applications; and existing tools, mechanisms, and systems in practice. Each chapter is independent from the other chapters, allowing users to read any chapter directly. After examining the practical side of Big Data, this book presents theoretical perspectives. The theoretical research ranges from Big Data representation, modeling and topology to distribution and dimension reducing. Chapters also investigate the many disciplines that involve Big Data, such as statistics, data mining, machine learning, networking, algorithms, security and differential geometry. The last section of this book introduces Big Data applications from different communities, such as business, engineering and science. Big Data Concepts, Theories and Applications is designed as a reference for researchers and advanced level students in computer science, electrical engineering and mathematics. Practitioners who focus on information systems, big data, data mining, business analysis and other related fields will also find this material valuable.
Big Data: Conceptual Analysis and Applications (Studies in Big Data #58)
by Michael Z. Zgurovsky Yuriy P. ZaychenkoThe book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used. Application of hybrid neuro-fuzzy networks for analyzing stock markets was presented. The analysis of big historical, economic and physical data revealed the hidden Fibonacci pattern about the course of systemic world conflicts and their connection with the Kondratieff big economic cycles and the Schwabe–Wolf solar activity cycles. The book is useful for system analysts and practitioners working with complex systems in various spheres of human activity.
Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners (Wiley and SAS Business Series)
by Jared DeanWith big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners (Wiley and SAS Business Series)
by Jared DeanWith big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
Big Data, Databases and "Ownership" Rights in the Cloud (Perspectives in Law, Business and Innovation)
by Marcelo Corrales CompagnucciTwo of the most important developments of this new century are the emergence of cloud computing and big data. However, the uncertainties surrounding the failure of cloud service providers to clearly assert ownership rights over data and databases during cloud computing transactions and big data services have been perceived as imposing legal risks and transaction costs. This lack of clear ownership rights is also seen as slowing down the capacity of the Internet market to thrive. Click-through agreements drafted on a take-it-or-leave-it basis govern the current state of the art, and they do not allow much room for negotiation. The novel contribution of this book proffers a new contractual model advocating the extension of the negotiation capabilities of cloud customers, thus enabling an automated and machine-readable framework, orchestrated by a cloud broker.Cloud computing and big data are constantly evolving and transforming into new paradigms where cloud brokers are predicted to play a vital role as innovation intermediaries adding extra value to the entire life cycle. This evolution will alleviate the legal uncertainties in society by means of embedding legal requirements in the user interface and related computer systems or its code. This book situates the theories of law and economics and behavioral law and economics in the context of cloud computing and takes database rights and ownership rights of data as prime examples to represent the problem of collecting, outsourcing, and sharing data and databases on a global scale. It does this by highlighting the legal constraints concerning ownership rights of data and databases and proposes finding a solution outside the boundaries and limitations of the law. By allowing cloud brokers to establish themselves in the market as entities coordinating and actively engaging in the negotiation of service-level agreements (SLAs), individual customers as well as small and medium-sized enterprises could efficiently and effortlessly choose a cloud provider that best suits their needs. This approach, which the author calls “plan-like architectures,” endeavors to create a more trustworthy cloud computing environment and to yield radical new results for the development of the cloud computing and big data markets.
Big Data, Datafizierung und digitale Artefakte (Medienbildung und Gesellschaft #42)
by Johannes Fromme Dan Verständig Stefan Iske Katrin WildeDer Band fokussiert Entwicklungen und Problemstellungen rund um das Verhältnis des Menschen zu Daten und Zahlen sowie die daran geknüpften Implikationen für Medien, Bildung und Gesellschaft. Ausgangspunkte bilden hierbei auf der einen Seite Big Data und Tendenzen der Datafizierung sozialer Prozesse, auf der anderen Seite Transformationen des Ästhetischen im Hinblick auf kreativ-ästhetische Praktiken. Der Band versammelt dabei unterschiedliche theoretische Positionen, die sich gemeinsam an zentralen Fragen der Medienbildung und kulturellen Bildung im digitalen Zeitalter orientieren.
The Big Data-Driven Digital Economy: Artificial and Computational Intelligence (Studies in Computational Intelligence #974)
by Abdalmuttaleb M. A. Musleh Al-SartawiThis book shows digital economy has become one of the most sought out solutions to sustainable development and economic growth of nations. This book discusses the implications of both artificial intelligence and computational intelligence in the digital economy providing a holistic view on AI education, economics, finance, sustainability, ethics, governance, cybersecurity, blockchain, and knowledge management. Unlike other books, this book brings together two important areas, intelligence systems and big data in the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations. The chapters hereby focus on how societies can take advantage and manage data, as well as the limitations they face due to the complexity of resources in the form of digital data and the intelligence which will support economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, students, economic development strategies, and the efforts made by the UN towards achieving their sustainability goals.
Big Data-driven World: Legislation Issues and Control Technologies (Studies in Systems, Decision and Control #181)
by Alla G. KravetsThis book examines the methodological foundations of the Big Data-driven world, formulates its concept within the frameworks of modern control methods and theories, and approaches the peculiarities of Control Technologies as a specific sphere of the Big Data-driven world, distinguished in the modern Digital Economy. The book studies the genesis of mathematical and information methods’ transition from data analysis & processing to knowledge discovery and predictive analytics in the 21st century. In addition, it analyzes the conditions of development and implementation of Big Data analysis approaches in investigative activities and determines the role and meaning of global networks as platforms for the establishment of legislation and regulations in the Big Data-driven world.The book examines that world through the prism of Legislation Issues, substantiate the scientific and methodological approaches to studying modern mechanisms of terrorism and extremism counteraction in the conditions of new challenges of dissemination and accessibility of socially dangerous information. Systematization of successful experience of the Big Data solutions implementation in the different countries and analyze causal connections of the Digital Economy formation from the positions of new technological challenges is performed.The book’s target audience includes scientists, students, PhD and Master students who conduct scientific research on the topic of Big Data not only in the field of IT& data science, but also in connection with legislative regulation aspects of the modern information society. It also includes practitioners and experts, as well as state authorities and representatives of international organizations interested in creating mechanisms for implementing Digital Economy projects in the Big Data-driven world.