Abstract
The pervasive nature of big data technologies as witnessed in industry services and everyday life has given rise to an emergent, data-focused economy stemming from many aspects of industrial applications. The richness and vastness of these services are creating unprecedented research opportunities in a number of industrial fields including public health, urban studies, economics, finance, social science, and geography. We are moving towards the era of Big Data Services, which are deployed in a multi-scale complex distributed architecture. These services can be formed a high-level computational intelligence based on emerging analytical techniques such as big data analytics and web analytics. In this context, computational intelligence employs software tools from advanced analytics disciplines such as data mining, predictive analytics, and machine learning. At the same time, it becomes increasingly important to anticipate technical and practical challenges and to identify best practices learned through experience. This special session has included nine papers, and a brief summary about each paper is presented as follows. TS - RIS
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CITATION STYLE
Zhou, Z., Gaaloul, W., Hung, P. C. K., Shu, L., & Tan, W. (2016). IEEE Access Special Session Editorial: Big Data Services and Computational Intelligence for Industrial Systems. IEEE Access, 3, 3085–3088. https://doi.org/10.1109/access.2016.2516178
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