IEEE Access Special Section Editorial: AI-Driven Big Data Processing: Theory, Methodology, and Applications

Abstract

With the rapid development of network infrastructures and personal electronic products, big data generated from the Internet, sensing networks, and other equipment are rapidly growing and have received increasing attention in recent years. Recently, artificial intelligence (AI)-driven big data processing technologies based on pattern recognition, machine learning, and deep learning have been intensively applied to dealing with large-scale heterogeneous data. However, challenges still exist in the development of AI-driven big data processing. In order to meet the existing challenges, it is important to consider how to analyze and process big data in a way that is more effective and reduces costs, how to discover and understand knowledge from the data, and how to generalize and transfer these discoveries into other application fields.