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Data Mining with Big Data

delete2014-01-01
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PRE
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X
Xindong Wu *
X
Xingquan Zhu
G
Gongqing Wu
W
Wei Ding
DOI:10.1109/TKDE.2013.109delete
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摘要

摘要

En 中文
Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.
Keyword:
Big Data
data mining
heterogeneity
autonomous sources
complex and evolving associations
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期刊

IEEE Transactions on Knowledge and Data Engineering 封面图
IEEE Transactions on Knowledge and Data Engineering
IF:
10.4
论文数:
6.9K
被引数:
3.2W

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H
hefei university of technology
学者数:
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论文数: 1.7W
被引数: 35
State University System of Florida 封面图
State University System of Florida
学者数:
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论文数: 10.9W
被引数: 130
F
Florida Atlantic University
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3.2K
论文数: 2.5K
被引数: 4.8K
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