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Titlebook: Big Data and Visual Analytics; Sang C. Suh,Thomas Anthony Conference proceedings 2017 Springer International Publishing AG 2017 Big data.B

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發(fā)表于 2025-3-25 04:51:27 | 只看該作者
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發(fā)表于 2025-3-25 11:02:07 | 只看該作者
Scalable Gene Sequence Analysis on Spark,in memory. Experiments detailed in this chapter make use of publicly available 1000 genome Variant Calling Format (VCF) data (Size 1.2TB) as input. The input data are analyzed using Spark and the end results are evaluated to measure the scalability and performance of the system.
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發(fā)表于 2025-3-25 12:48:27 | 只看該作者
Big Sensor Data Acquisition and Archiving with Compression,ed. Next, a quality-adjustable sensor data archiving is discussed, which compresses an entire collection of sensor data efficiently without compromising key features. Considering data aging aspect, this archiving scheme is capable of decreasing data fidelity gradually to secure more storage space.
24#
發(fā)表于 2025-3-25 18:03:18 | 只看該作者
Conference proceedings 2017 and visual analytics...This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference..
25#
發(fā)表于 2025-3-25 21:24:33 | 只看該作者
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發(fā)表于 2025-3-26 03:34:04 | 只看該作者
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發(fā)表于 2025-3-26 04:58:11 | 只看該作者
https://doi.org/10.1007/978-3-319-63917-8Big data; Big data applications; Big data architecture; Business analytics; Data mining and knowledge di
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發(fā)表于 2025-3-26 12:24:11 | 只看該作者
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發(fā)表于 2025-3-26 13:35:45 | 只看該作者
Introduction to Evolutionary GenomicsBig data Analytics and data science helps finance in combining business research expertise, scientific processes, quantitative analytics and system infrastructure to distill knowledge and insights from internal/external, structured/unstructured data.
30#
發(fā)表于 2025-3-26 18:45:43 | 只看該作者
Big Data Analytics and Visualization: Finance,Big data Analytics and data science helps finance in combining business research expertise, scientific processes, quantitative analytics and system infrastructure to distill knowledge and insights from internal/external, structured/unstructured data.
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