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Big Data Applications and Use Cases: International Series on Computer, Entertainment and Media Technology

Editat de Patrick C. K. Hung
en Limba Engleză Hardback – 25 mai 2016
This book presents different use cases in big data applications and related practical experiences. Many businesses today are increasingly interested in utilizing big data technologies for supporting their business intelligence so that it is becoming more and more important to understand the various practical issues from different practical use cases. This book provides clear proof that big data technologies are playing an ever increasing important and critical role in a new cross-discipline research between computer science and business. 
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Specificații

ISBN-13: 9783319301440
ISBN-10: 3319301446
Pagini: 250
Ilustrații: VI, 214 p. 70 illus., 62 illus. in color.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.49 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria International Series on Computer, Entertainment and Media Technology

Locul publicării:Cham, Switzerland

Cuprins

Introduction to Big Data.- A Bloom Filter-based Approach for Supporting the Representation and Membership Query of Multidimensional Dataset.- Automatic Speech and Singing Discrimination for Audio Data Indexing.- Exploring the Feature Selection-based Data Analytics Solutions for Text Mining Online Communities by Investigating the Influential Factors - A Case Study of Programming CQA in Stack Overflow.- Temporal Event Tracing on Big Healthcare Data Analytics.- Unstructured Data, NoSQL, and Terms Analytics.- VLAB-C: Collaborative Virtual Laboratory in Cloud Computing and its Applications.- A Crowdsourcing Social Network Service for Social Enterprise Innovation.- Self-adaptive Parameters Optimization for Incremental Classification in Big Data Using Neural Network.- VLAB-C: Collaborative Virtual Laboratory in Cloud Computing and its Applications.- Case Studies of Government Use of Big Data in Latin America: Brazil and Mexico.

Recenzii

“This book would be of interest to researchers and practitioners in the data analytics field. It examines the characteristics of big data; the uses of big data, including government, marketing, insurance, the Internet of Things, and healthcare; and different analytic approaches. The book is reasonably well organized and provides examples of the application of data analysis to various public and private sector organizations. Sufficient references are provided.” (Computing Reviews, August, 2017) 

Notă biografică

Patrick C. K. Hung is an Associate Professor at the Faculty of Business and Information Technology in University of Ontario Institute of Technology, Canada and an Honorary International Chair Professor at the Department of Electronic Engineering in National Taipei University of Technology, Taiwan. Patrick has worked with Boeing Research and Technology on aviation services-related research with two patents on mobile network dynamic workflow system. He is also a Visiting Professor at University of Sao Paulo, Brazil. In addition, he was an Adjunct Professor at Wuhan University, a Visiting Professor at the Shizuoka University and University of Aizu in Japan, a Guest Professor in University of Innsbruck in Austria, University of Trento and University of Milan in Italy. Before that, he was a Research Scientist with Commonwealth Scientific and Industrial Research Organization in Australia as well as he worked as a software engineer in industry in North America. He is a founding committee member of the IEEE International Conference of Web Services (ICWS), IEEE International Conference on Services Computing (SCC), and IEEE BigData Congress (BigData Congress). He is also an Associate Editor of the IEEE Transactions on Services Computing, and a Coordinating Editor of the Information Systems Frontiers.

Caracteristici

Outlines different use cases for big data applications and technologies in supporting business intelligence, a cross discipline of computer science and business Includes contributions from leading researchers and practitioners, providing readers with a theoretical and practical understanding of the challenges facing big data today and beyond Surveys big data and dataset core concepts and principles Includes supplementary material: sn.pub/extras