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CIBD 2016 - 2016 IEEE Symposium on Computational Intelligence in Big Data (IEEE CIBD'16)

Date2016-12-06 - 2016-12-09


VenueAthens, Greece Greece



Topics/Call fo Papers

IEEE CIBD’2016 will be held simultaneously with other symposia and workshops in one location at the 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016). This international event promotes all aspects of the theory and applications of computational intelligence. Sponsored by the IEEE Computational Intelligence Society, this event will attract top scientists, researchers, professionals, practitioners and students from around the world. The registration to SSCI 2016 will allow participants to attend all the symposia, including the complete set of the proceedings of all the meetings, coffee breaks, lunches, and the banquet.
Scope and Topics
IEEE CIBD’2016 will bring together scientists, engineers, researchers and students from around the world to present recent advances, explore challenges and opportunities in the application of Computational Intelligence (CI) techniques to the emerging and exciting field of Big Data and data sciences. This conference will provide a forum to present recent results in CI algorithms, software and systems for big data analytics, discuss the practical and theoretical challenges in big data, and explore CI solutions to tackle these challenges and issues.
IEEE CIBD’2016 solicits papers that report new research results that apply CI technologies, such as deep learning, neural networks and learning algorithms, fuzzy systems, evolutionary computation, and other emerging techniques to Big Data, ranging from theory, methodologies and algorithms for handling the 3Vs (Volume, Variety, and Velocity) of big data, to their applications to the development of big data analytics systems. Successful applications of big data in industries are also encouraged to participate in this event.
Topics of IEEE CIBD’2016 include but are not limited to:
Integrative analytics of diverse data resources
Integration of structured and unstructured data
Deep learning of big data
Big data in healthcare
Big data in industrial internet of things
Big data in future media
Big data in finance and economy
Big data in public services
Big data in social media
Big data in intelligent robotics
Big data driven new business
Extracting understanding from distributed, diverse and large-scale data resources
Extracting understanding from real-time large-scale data streams
Predictive analytics and in-memory analytics
New information infrastructure for big data
Big data visualization and visual data analytics
Semantic technologies for big data
Scalable learning techniques for big data
Optimization of complex systems involving big data
Data governance and management in big data
Human-computer interaction and collaboration in big data
Big data and cloud computing
Applications of big data, such as industrial processes , business intelligence, healthcare, bioinformatics and security
Special Sessions
Proposals for special session and tutorials are encouraged. Please send your proposal to one of the co-chairs by April 18, 2016.
Yonghong Peng
University of Bradford, UK
Yaochu Jin
University of Surrey, UK
Marios Polycarpou
University of Cyprus, Cyprus

Last modified: 2016-01-11 21:35:29