Journal
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
Volume 26, Issue 1, Pages 97-107Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TKDE.2013.109
Keywords
Big Data; data mining; heterogeneity; autonomous sources; complex and evolving associations
Categories
Funding
- National 863 Program of China [2012AA011005]
- National 973 Program of China [2013CB329604]
- National Natural Science Foundation of China [NSFC 61229301, 61273297, 61273292]
- US National Science Foundation [NSF CCF-0905337]
- Australian Research Council (ARC) [FT100100971, DP130102748]
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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.
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