CIBD 2017 - 2017 IEEE Symposium on Computational Intelligence in Big Data (IEEE CIBD'17)

The IEEE CIBD 2017 will bring together international scientists, researchers and professionals to present and discuss the current challenges and opportunities in big data related to computational intelligence (CI). The organisers welcome presentation of recent results relating to CI algorithms, software, systems and architecture, data analytics, current challenges, and new and emerging applications. Presentations relating to industry, novel applications and emerging CI areas in BG are strongly encouraged.
Specific topics include, but are not limited to:
- Novel CI methods of big data acquisition
- CI in distributed computing of big data
- Memory efficient CI algorithms relating to reading, processing or analysing big data
- Data mining in big data
- Deep learning in big data
- Integration of big data, such as multi-modal, multi-fidelity, structured and unstructured data
- Big data in industry
- Big data in healthcare
- Big data and the internet of things
- Big data in the future of media and social media
- Big data in finances and economy
- Big data in public services
- Big data in intelligent robotics
- Big data driven business or industry
- Extracting understanding from distributed, diverse and large-scale data resources
- Real time analysis of large data streams
- Predictive analysis and in-memory analytics
- Dimensionality reduction and analysis of large and complex data
- New information infrastructures
- Visualisation of big data and visual data analytics
- Semantics technologies for big data
- Scalable learning in big data
- Optimisation of big data in complex systems
- Data governance and management
- CI in curation of big data
- Human-computer interaction and collaboration in big data
- Big data and cloud computing
- Applications of big data, such as industrial process, business intelligence, healthcare, bioinformatics and security.
l Symposium Chairs:
Yaochu Jin, University of Surrey, UK
Spencer Thomas, National Physical Laboratory, UK
Lazaros Polymenakos , IBM Watson, USA
Marios Polycarpou, University of Cyprus, Cyprus