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NEMICO: Mining Network Data through Cloud-Based Data Mining Techniques

机译:NEMICO:通过基于云的数据挖掘技术挖掘网络数据

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Thanks to the rapid advances in Internet-based applications, data acquisition and storage technologies, petabyte-sized network data collections are becoming more and more common, thus prompting the need for scalable data analysis solutions. By leveraging today's ubiquitous many-core computer architectures and the increasingly popular cloud computing paradigm, the applicability of data mining algorithms to these large volumes of network data can be scaled up to gain interesting insights. This paper proposes NEMICO, a comprehensive Big Data mining system targeted to network traffic flow analyses (e.g., Traffic flow characterization, anomaly detection, multiple-level pattern mining). NEMICO comprises new approaches that contribute to a paradigm-shift in distributed data mining by addressing most challenging issues related to Big Data, such as data sparsity, horizontal scaling, and parallel computation.
机译:由于基于Internet的应用程序,数据获取和存储技术的飞速发展,PB级的网络数据收集变得越来越普遍,因此引发了对可伸缩数据分析解决方案的需求。通过利用当今无处不在的多核计算机体系结构和日益流行的云计算范例,可以扩大数据挖掘算法在海量网络数据上的适用性,从而获得有趣的见解。本文提出了NEMICO,这是一种针对网络流量分析(例如流量流量表征,异常检测,多层模式挖掘)的综合大数据挖掘系统。 NEMICO包含一些新方法,这些新方法通过解决与大数据有关的最具挑战性的问题,例如数据稀疏性,水平缩放和并行计算,从而为分布式数据挖掘的范式转变做出了贡献。

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