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Author: Bo Hu
Publisher: Springer Nature
ISBN: 3031235010
Category : Computers
Languages : en
Pages : 101
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Book Description
This book constitutes the proceedings of the 11th International Conference on Big Data, BigData 2022, held as part of the Services Conference Federation, SCF 2022, held in Honolulu, HI, USA, in December 2022. The 4 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 16 submissions. The 2022 International Congress on Big Data (BigData 2022) aims to provide an international forum that formally explores various business insights of all kinds of value-added "services". Big Data is a key enabler of exploring business insights and economics of services.
Author: Yong Zhang
Publisher: Springer Nature
ISBN: 3031770889
Category :
Languages : en
Pages : 145
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Book Description
Author: Bo Hu
Publisher: Springer Nature
ISBN: 3031235010
Category : Computers
Languages : en
Pages : 101
Get Book Here
Book Description
This book constitutes the proceedings of the 11th International Conference on Big Data, BigData 2022, held as part of the Services Conference Federation, SCF 2022, held in Honolulu, HI, USA, in December 2022. The 4 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 16 submissions. The 2022 International Congress on Big Data (BigData 2022) aims to provide an international forum that formally explores various business insights of all kinds of value-added "services". Big Data is a key enabler of exploring business insights and economics of services.
Author: Sherif Sakr
Publisher: CRC Press
ISBN: 1466581506
Category : Computers
Languages : en
Pages : 640
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Book Description
Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book’s second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.
Author: Katharine G. Abraham
Publisher: University of Chicago Press
ISBN: 022680125X
Category : Business & Economics
Languages : en
Pages : 502
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Book Description
Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.
Author: Parikshit N Mahalle
Publisher: CRC Press
ISBN: 1040031137
Category : Computers
Languages : en
Pages : 309
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Book Description
This book explores the need for a data‐centric AI approach and its application in the multidisciplinary domain, compared to a model‐centric approach. It examines the methodologies for data‐centric approaches, the use of data‐centric approaches in different domains, the need for edge AI and how it differs from cloud‐based AI. It discusses the new category of AI technology, "data‐centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, data‐centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods. • Includes a collection of case studies with experimentation results to adhere to the practical approaches • Examines challenges in dataset generation, synthetic datasets, analysis, and prediction algorithms in stochastic ways • Discusses methodologies to achieve accurate results by improving the quality of data • Comprises cases in healthcare and agriculture with implementation and impact of quality data in building AI applications
Author: Shaoxu Song
Publisher: Springer Nature
ISBN: 3031271777
Category : Computers
Languages : en
Pages : 154
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Book Description
This book examines the recent trend of extending data dependencies to adapt to rich data types in order to address variety and veracity issues in big data. Readers will be guided through the full range of rich data types where data dependencies have been successfully applied, including categorical data with equality relationships, heterogeneous data with similarity relationships, numerical data with order relationships, sequential data with timestamps, and graph data with complicated structures. The text will also discuss interesting constraints on ordering or similarity relationships contained in novel classes of data dependencies in addition to those in equality relationships, e.g., considered in functional dependencies (FDs). In addition to exploring the concepts of these data dependency notations, the book investigates the extension relationships between data dependencies, such as conditional functional dependencies (CFDs) that extend conventional functional dependencies (FDs). This forms in the book a family tree of extensions, mostly rooted in FDs, that help illuminate the expressive power of various data dependencies. Moreover, the book points to work on the discovery of dependencies from data, since data dependencies are often unlikely to be manually specified in a traditional way, given the huge volume and high variety in big data. It further outlines the applications of the extended data dependencies, in particular in data quality practice. Altogether, this book provides a comprehensive guide for readers to select proper data dependencies for their applications that have sufficient expressive power and reasonable discovery cost. Finally, the book concludes with several directions of future studies on emerging data.
Author: Neeraj Kumar
Publisher: CRC Press
ISBN: 1000163490
Category : Computers
Languages : en
Pages : 360
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Book Description
Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.
Author: Yasser Mansour
Publisher: Springer Nature
ISBN: 9819783453
Category :
Languages : en
Pages : 493
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Book Description
Author: Xin-She Yang
Publisher: Springer Nature
ISBN: 981993236X
Category : Technology & Engineering
Languages : en
Pages : 1119
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Book Description
This book gathers selected high-quality research papers presented at the Eighth International Congress on Information and Communication Technology, held at Brunel University, London, on 20–23 February 2023. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The work is presented in four volumes.
Author: Kejiang Ye
Publisher: Springer Nature
ISBN: 3031234987
Category : Computers
Languages : en
Pages : 131
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Book Description
This book constitutes the proceedings of the 15th International Conference on Cloud Computing, CLOUD 2022, held as part of the Services Conference Federation, SCF 2022, held in Honolulu, HI, USA, in December 2022. The 8 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 15 submissions. The International Conference on Cloud Computing (CLOUD) has been a prime international forum for both researchers and industry practitioners to exchange the latest fundamental advances in the state of the art and practice of cloud computing, identify emerging research topics, and define the future of cloud computing. All topics regarding cloud computing align with the theme of CLOUD.
