TY - JOUR TI - Data mining with big data AU - Wu, Xindong AU - Zhu, Xingquan AU - Wu, Gong-Qing AU - Ding, Wei T2 - IEEE Transactions on Knowledge and Data Engineering AB - 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. DA - 2014/// PY - 2014 DO - 10.1109/TKDE.2013.109 DP - IEEE Xplore VL - 26 IS - 1 SP - 97 EP - 107 LA - en SN - 1558-2191 KW - Big data KW - Data science ER -