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Record Nr. |
UNINA9910299052703321 |
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Autore |
Chen Min |
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Titolo |
Big Data : Related Technologies, Challenges and Future Prospects / / by Min Chen, Shiwen Mao, Yin Zhang, Victor C.M. Leung |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
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ISBN |
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Edizione |
[1st ed. 2014.] |
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Descrizione fisica |
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1 online resource (100 p.) |
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Collana |
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SpringerBriefs in Computer Science, , 2191-5768 |
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Disciplina |
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Soggetti |
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Computers |
Database management |
Computer communication systems |
Application software |
Data mining |
Information Systems and Communication Service |
Database Management |
Computer Communication Networks |
Information Systems Applications (incl. Internet) |
Data Mining and Knowledge Discovery |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Introduction -- Related Technologies -- Big Data Generation and Acquisition -- Big Data Storage -- Big Data Analysis -- Big Data Applications -- Open Issues and Outlook. |
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Sommario/riassunto |
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This Springer Brief provides a comprehensive overview of the background and recent developments of big data. The value chain of big data is divided into four phases: data generation, data acquisition, data storage and data analysis. For each phase, the book introduces the general background, discusses technical challenges and reviews the latest advances. Technologies under discussion include cloud computing, Internet of Things, data centers, Hadoop and more. The authors also explore several representative applications of big data such as enterprise management, online social networks, healthcare and medical applications, collective intelligence and smart grids. This book |
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concludes with a thoughtful discussion of possible research directions and development trends in the field. Big Data: Related Technologies, Challenges and Future Prospects is a concise yet thorough examination of this exciting area. It is designed for researchers and professionals interested in big data or related research. Advanced-level students in computer science and electrical engineering will also find this book useful. |
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