DocumentCode :
10087
Title :
Data mining with big data
Author :
Xindong Wu ; Xingquan Zhu ; Gong-Qing Wu ; Wei Ding
Author_Institution :
Sch. of Comput. Sci. & Inf. Eng., Hefei Univ. of Technol., Hefei, China
Volume :
26
Issue :
1
fYear :
2014
fDate :
Jan. 2014
Firstpage :
97
Lastpage :
107
Abstract :
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.
Keywords :
data mining; user modelling; Big Data processing model; Big Data revolution; HACE theorem; data collection capacity; data driven model; data mining; data storage; demand driven aggregation; growing data sets; information sources; networking; user interest modeling; Data handling; Data models; Data privacy; Data storage systems; Distributed databases; Information management; Big Data; autonomous sources; complex and evolving associations; data mining; heterogeneity;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/TKDE.2013.109
Filename :
6547630
Link To Document :
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