HARNESSING BIG DATA: ADVANCES AND CHALLENGES IN DATA MINING
Keywords:
Big Data, Data Mining, Source Of Information, Data Storage, User Privacy, Technological Domains, Big Data Processing, Learning Algorithms, Complex Network, Cognitive Domains, Complex Data, Kinetic Data, Massive Data, Knowledge Discovery, Data Mining Methods, Decentralized Control, Map Reduce, Data Mining Algorithms.Abstract
Big Data concerns 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 is now rapidly expanding in all science and
engineering domains, including physical, biological and biomedical sciences. This article 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.
