| 書目名稱 | Large-Scale Data Analytics | | 編輯 | Aris Gkoulalas-Divanis,Abderrahim‘Labbi | | 視頻video | http://file.papertrans.cn/582/581385/581385.mp4 | | 概述 | Provides cutting-edge research in large-scale data analytics from diverse scientific areas.Surveys varied subject areas and reports on individual results of research in the field.Shares many tips and | | 圖書封面 |  | | 描述 | .This edited book collects state-of-the-art research related to large-scale data analytics that has been accomplished over the last few years. This is among the first books devoted to this important area based on contributions from diverse scientific areas such as databases, data mining, supercomputing, hardware architecture, data visualization, statistics, and privacy..There is increasing need for new approaches and technologies that can analyze and synthesize very large amounts of data, in the order of petabytes, that are generated by massively distributed data sources. This requires new distributed architectures for data analysis. Additionally, the heterogeneity of such sources imposes significant challenges for the efficient analysis of the data under numerous constraints, including consistent data integration, data homogenization and scaling, privacy and security preservation. The authors also broaden reader understanding of emerging real-world applications in domains such as customer behavior modeling, graph mining, telecommunications, cyber-security, and social network analysis, all of which impose extra requirements for large-scale data analysis..Large-Scale Data Analytics. | | 出版日期 | Book 2014 | | 關鍵詞 | Big data; GPU programming; data mining; graph mining; hardware acceleration; high performance computing; l | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4614-9242-9 | | isbn_softcover | 978-1-4939-4225-1 | | isbn_ebook | 978-1-4614-9242-9 | | copyright | Springer Science+Business Media New York 2014 |
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