DocumentCode :
3613208
Title :
IEEE Access Special Session Editorial: Big Data Services and Computational Intelligence for Industrial Systems
Author :
Zhou, Zhangbing ; Gaaloul, Walid ; Hung, Patrick C. K. ; Shu, Lei ; Tan, Wei
Author_Institution :
, China University of Geosciences, Beijing, China
Volume :
3
fYear :
2015
fDate :
7/7/1905 12:00:00 AM
Firstpage :
3085
Lastpage :
3088
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.
Keywords :
Big data; Computational intelligence; Finance; Geography; Public healthcare; Special issues and sections;
fLanguage :
English
Journal_Title :
Access, IEEE
Publisher :
ieee
ISSN :
2169-3536
Type :
jour
DOI :
10.1109/ACCESS.2016.2516178
Filename :
7389477
Link To Document :
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