Big Data on Real-World Applications
Describes the importance of the Big Data era and how existing information systems are required to be adapted to face up the problems derived from the management of massive datasets.
Tag(s): Big Data
Publication date: 20 Jul 2016
ISBN-10: n/a
ISBN-13: 9789535124900
Paperback: 122 pages
Views: 9,963
Type: Book
Publisher: InTech
License: Creative Commons Attribution 3.0 Unported
Post time: 10 Nov 2016 05:00:00
Big Data on Real-World Applications
Describes the importance of the Big Data era and how existing information systems are required to be adapted to face up the problems derived from the management of massive datasets.
Publication date: 20 Jul 2016
ISBN-10: n/a
ISBN-13: 9789535124900
Paperback: 122 pages
Views: 9,963
Document Type: Book
Publisher: InTech
License: Creative Commons Attribution 3.0 Unported
Post time: 10 Nov 2016 05:00:00
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Soto, Luna, and Cano wrote:As technology advances, high volumes of valuable data are generated day by day in modern organizations. The management of such huge volumes of data has become a priority in these organizations, requiring new techniques for data management and data analysis in Big Data environments. These environments encompass many different fields including medicine, education data, and recommender systems. The aim of this book is to provide the reader with a variety of fields and systems where the analysis and management of Big Data are essential. This book describes the importance of the Big Data era and how existing information systems are required to be adapted to face up the problems derived from the management of massive datasets.
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About The Editor(s)
Alberto Cano is an assistant professor in the Department of Computer Science at the Virginia Commonwealth University, USA, where he heads the High-Performance Data Mining Lab. His research is focused on machine learning, data mining, soft computing, parallel computing, and general purpose GPU systems. He has published 17 articles in international journals, 12 contributions to international conferences, and 2 book chapters, and he has served as a member of the technical program committee in more than 60 international conferences.
Alberto Cano is an assistant professor in the Department of Computer Science at the Virginia Commonwealth University, USA, where he heads the High-Performance Data Mining Lab. His research is focused on machine learning, data mining, soft computing, parallel computing, and general purpose GPU systems. He has published 17 articles in international journals, 12 contributions to international conferences, and 2 book chapters, and he has served as a member of the technical program committee in more than 60 international conferences.
José María Luna received his PhD with a grade of summa cum laude in Computer Science by the University of Granada in January 2014. Dr. Luna is author of the book "Pattern Mining with Evolutionary Algorithms", published by Springer in 2016. He has published more than 30 papers in top ranked journals and international scientific conferences, and he is author of two book chapters. His research is focused on pattern mining, and he is interested in mining patterns on flexible data.
José María Luna received his PhD with a grade of summa cum laude in Computer Science by the University of Granada in January 2014. Dr. Luna is author of the book "Pattern Mining with Evolutionary Algorithms", published by Springer in 2016. He has published more than 30 papers in top ranked journals and international scientific conferences, and he is author of two book chapters. His research is focused on pattern mining, and he is interested in mining patterns on flexible data.
Sebastián Ventura is (associate) Professor of Computer Sciences and Artificial Intelligence in the University of Córdoba. His teaching is devoted to applied programming, artificial intelligence, bioinformatics in computer science engineering and data mining in doctoral studies. His research labor is developed as a member of the "Knowledge Discovery and Intelligent Systems" (KDIS) research group, and it is focused on soft computing, machine learning, data mining and its applications.
Sebastián Ventura is (associate) Professor of Computer Sciences and Artificial Intelligence in the University of Córdoba. His teaching is devoted to applied programming, artificial intelligence, bioinformatics in computer science engineering and data mining in doctoral studies. His research labor is developed as a member of the "Knowledge Discovery and Intelligent Systems" (KDIS) research group, and it is focused on soft computing, machine learning, data mining and its applications.