Big Data
Big Data
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DOI：
10.1109/mis.2017.32
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发表时间：
2017-03
期刊：
影响因子：
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通讯作者：
Weike Pan;Qiang Yang;C. Aggarwal;Christoph E. Koch
中科院分区：
文献类型：
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作者：
Weike Pan;Qiang Yang;C. Aggarwal;Christoph E. Koch
大数据已经成为我们社会大多数领域创新、重建和进步的推动力，并不断受到学术界、工业界和政府的研究人员和实践者的关注。然而，从理论基础、系统和技术到数据政策和标准，仍然存在许多挑战。本期特刊关注大数据如何跨越系统和应用领域，客座编辑的介绍介绍了他们从30篇提交的文章中选出的5篇文章，这些文章涵盖了广泛的有趣主题，包括大数据分析的特征选择、天文图像分析、大规模网络预测、在线URL过滤和大规模事务聚类。
Big data has been an enabler for innovation, reconstruction, and advancement of most sectors of our society, and it's receiving continuous and growing attention from researchers and practitioners in academia, industry, and government. There are, however, still lots of challenges spanning from theoretical foundations, systems, and technology to data policy and standards. This special issue focuses on how big data cuts across systems and applications arenas, and the guest editors' introduction describes the five articles they selected out of 30 submitted to cover a wide spectrum of interesting topics, including feature selection for big data analytics, astronomical image analysis, large-scale network prediction, online URL filtering, and massive transaction clustering.