Scalable and Efficient Data Mining with Big Data
Big knowledge concern large-volume, complex, growing knowledge sets with multiple, autonomous sources. With the quick development of networking, knowledge storage and also the knowledge assortment capability, huge knowledge area unit currently quickly increasing altogether science and engineering domains, together with physical, biological and medicine sciences. This paper presents a HACE theorem that characterizes the options of the large knowledge revolution and proposes a giant processing model, from the info mining perspective. This data-driven model involves demand-driven aggregation of data sources, mining and analysis, user interest modeling and security and privacy considerations.
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