%0 Journal Article %1 WuZhuEtAl14tkde %A Wu, Xindong %A Zhu, Xingquan %A Wu, Gong-Qing %A Ding, Wei %D 2014 %J IEEE Transactions on Knowledge and Data Engineering %K 01614 ieee paper ai data pattern recognition analysis processing information retrieval zzz.big %N 1 %P 97--107 %R 10.1109/TKDE.2013.109 %T Data Mining with Big Data %V 26 %X 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.

@article{WuZhuEtAl14tkde, 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.}, added-at = {2016-05-21T10:20:05.000+0200}, author = {Wu, Xindong and Zhu, Xingquan and Wu, Gong-Qing and Ding, Wei}, biburl = {https://www.bibsonomy.org/bibtex/2d8014df14696a60a134e0c2efe979f31/flint63}, doi = {10.1109/TKDE.2013.109}, file = {IEEE Digital Library:2014/WuZhuEtAl14tkde.pdf:PDF}, groups = {public}, interhash = {696615fed2d7fd2e9b4297075cb9885e}, intrahash = {d8014df14696a60a134e0c2efe979f31}, issn = {1041-4347}, journal = {IEEE Transactions on Knowledge and Data Engineering}, keywords = {01614 ieee paper ai data pattern recognition analysis processing information retrieval zzz.big}, month = {#jan#}, number = 1, pages = {97--107}, timestamp = {2018-04-16T12:36:20.000+0200}, title = {Data Mining with Big Data}, username = {flint63}, volume = 26, year = 2014 }