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Titlebook: Big Data Applications and Use Cases; Patrick C. K. Hung Book 2016 Springer International Publishing Switzerland 2016 Big data architecture

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期刊全稱Big Data Applications and Use Cases
影響因子2023Patrick C. K. Hung
視頻videohttp://file.papertrans.cn/186/185631/185631.mp4
發(fā)行地址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 res
學(xué)科分類International Series on Computer, Entertainment and Media Technology
圖書封面Titlebook: Big Data Applications and Use Cases;  Patrick C. K. Hung Book 2016 Springer International Publishing Switzerland 2016 Big data architecture
影響因子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.?.
Pindex Book 2016
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International Series on Computer, Entertainment and Media Technologyhttp://image.papertrans.cn/b/image/185631.jpg
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Derivatives and Differentiation,nal dataset. The paper presents a novel data structure based on Bloom filter for the multidimensional data representation. We further give the theoretical analysis and experimental evaluations of the algorithm. Results show that the algorithm can achieve the same false positive rate when dealing wit
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https://doi.org/10.1007/0-387-34228-1fact, CQA services gained much popularity recently compared to other Internet services in obtaining and exchanging information. Stack Overflow is an example of such a service that targets programmers and software developers. In general, most questions in Stack Overflow are usually ended up with an a
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Systems of Ordinary Differential Equations,L), a patient-driven data architecture is suggested to enable the rapid storing and flexible expansion of data. Thus, the schema differences of various hospitals can be overcome, and the flexibility for field alterations and addition is ensured. The timeline mode can easily be used to generate a vis
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