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About this product
- DescriptionAs today's organizations are capturing exponentially larger amounts of data than ever, w is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired kwledge to achieve competitive advantages. Presenting the contributions of leading experts in their respective fields, Big Data: Algorithms, Analytics, and Applications bridges the gap between the vastness of Big Data and the appropriate computational methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data, better analytical strategies to digest data, and representative applications in diverse fields, such as medicine, science, and engineering. The book is organized into five main sections: *Big Data Management-considers the research issues related to the management of Big Data, including indexing and scalability aspects *Big Data Processing-addresses the problem of processing Big Data across a wide range of resource-intensive computational settings *Big Data Stream Techniques and Algorithms-explores research issues regarding the management and mining of Big Data in streaming environments *Big Data Privacy-focuses on models, techniques, and algorithms for preserving Big Data privacy *Big Data Applications-illustrates practical applications of Big Data across several domains, including finance, multimedia tools, biometrics, and satellite Big Data processing Overall, the book reports on state-of-the-art studies and achievements in algorithms, analytics, and applications of Big Data. It provides readers with the basis for further efforts in this challenging scientific field that will play a leading role in next-generation database, data warehousing, data mining, and cloud computing research. It also explores related applications in diverse sectors, covering techlogies for media/data communication, elastic media/data storage, cross-network media/data fusion, and SaaS.
- Author BiographyKuan-Ching Li is a professor in the Department of Computer Science and Information Engineering at Providence University, Taiwan. He was department chair in 2009, has been special assistant to the university president since 2010, and was appointed vice dean for the Office of International and Cross-Strait Affairs (OIA) in 2014. He earned a PhD in 2001 from the University of Sao Paulo, Brazil. Dr. Li is a recipient of awards from NVIDIA, the Ministry of Education (MOE)/Taiwan, and the Ministry of Science and Technology (MOST)/Taiwan. He also received guest professorships at universities in China, including Xiamen University (XMU), Huazhong University of Science and Technology (HUST), Lanzhou University (LZU), Shanghai University (SHU), Anhui University of Science and Technology (AUST), and Lanzhou Jiaotong University (LZJTU). He has been involved actively in conferences and workshops as a program/general/steering conference chairman and in numerous conferences and workshops as a program committee member, and he has organized numerous conferences related to high-performance computing and computational science and engineering. Dr. Li is the editor in chief of the technical publications International Journal of Computational Science and Engineering (IJCSE), International Journal of Embedded Systems (IJES), and International Journal of High Performance Computing and Networking (IJHPCN), all published by Interscience. He also serves on a number of journals' editorial boards and guest editorships. In addition, he has been acting as editor/coeditor of several technical professional books, published by CRC Press and IGI Global. His topics of interest include networked computing, GPU computing, parallel software design, and performance evaluation and benchmarking. Dr. Li is a member of the Taiwan Association of Cloud Computing (TACC), a senior member of the IEEE, and a fellow of the IET. Hai Jiang is an associate professor in the Department of Computer Science at Arkansas State University, United States. He earned a BS at Beijing University of Posts and Telecommunications, China, and MA and PhD degrees at Wayne State University. His research interests include parallel and distributed systems, computer and network security, high-performance computing and communication, big data, and modeling and simulation. Dr. Jiang has published one book and several research papers in major international journals and conference proceedings. He has served as a US National Science Foundation proposal review panelist and a US Department of Energy (DoE) Smart Grid Investment Grant (SGIG) reviewer multiple times. He serves as an editor for the International Journal of High Performance Computing and Networking (IJHPCN); a regional editor for the International Journal of Computational Science and Engineering (IJCSE) as well as the International Journal of Embedded Systems (IJES); an editorial board member for the International Journal of Big Data Intelligence (IJBDI), the Scientific World Journal (TSWJ), the Open Journal of Internet of Things (OJIOT), and the GSTF Journal on Social Computing (JSC); and a guest editor for the IEEE Systems Journal, International Journal of Ad Hoc and Ubiquitous Computing, Cluster Computing, and The Scientific World Journal for multiple special issues. He has also served as a general chair or program chair for some major conferences/workshops (CSE, HPCC, ISPA, GPC, ScalCom, ESCAPE, GPU-Cloud, FutureTech, GPUTA, FC, SGC). He has been involved in 90 conferences and workshops as a session chair or as a program committee member, including major conferences such as AINA, ICPP, IUCC, ICPADS, TrustCom, HPCC, GPC, EUC, ICIS, SNPD, TSP, PDSEC, SECRUPT, and ScalCom. He has reviewed six cloud computing-related books (Distributed and Cloud Computing, Virtual Machines, Cloud Computing: Theory and Practice, Virtualized Infrastructure and Cloud Services Management, Cloud Computing: Technologies and Applications Programming, The Basics of
- PublisherApple Academic Press Inc.
- Date of Publication07/02/2015
- SubjectComputing: Professional & Programming
- Series TitleChapman & Hall/CRC Big Data Series
- Place of PublicationOakville
- Country of PublicationCanada
- ImprintApple Academic Press Inc.
- Content Note155 black & white illustrations, 15 black & white tables
- Weight1043 g
- Width178 mm
- Height254 mm
- Spine36 mm
- Edited byAlfredo Cuzzocrea,Hai Jiang,Kuan-Ching Li,Laurence T. Yang
- Format DetailsUnsewn / adhesive bound
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