Computational Aspects of Big Data Analysis (CABDA 2015)


The Big Data paradigm is one of the main science and technology challenges of today. Big data includes various data sets that are too large or too complex for efficient processing and analysis using traditional as well as unconventional algorithms and tools. The challenge is to derive value from signals buried in an avalanche of noise arising from challenging data volume, flow and validity. The cybernetics challenges are as varied as they are important. Whether searching for influential nodes in huge networks, segmenting graphs into meaningful communities, modelling uncertainties in health trends for individual patients, controlling of complex systems, linking data bases with different levels of granularity in space and time, unbiased sampling, connecting with infrastructure involving sensors, privacy protection and high performance computing, answers to these questions are the key to competitiveness and leadership in this field. This event will highlight current challenges in cybernetics methodology alongside new problems arising from Big Data applications.

This session, organized by IEEE SMC TC on Big Data Computing, aims at disseminating the latest results in the overlapping fields of big data processing, analysis, and mining. It will bring together big data researchers and practitioners to discuss theoretical and practical aspects of latest advances, algorithms, and applications in this field.

List of topics:

  • traditional and emerging methods for big data
  • machine learning for big data
  • intelligent and unconventional methods for big data
  • search and optimization for big data
  • parallel, accelerated, and distributed big data analysis
  • high performance computing for big data
  • novel hardware and software architectures for big data
  • real-world applications and success stories of big data analysis
  • Optimal and dynamic sampling
  • Uncertainty modelling & generalisation error bounds
  • Network analysis & community finding
  • Graph & web mining methods
  • Trend tracking & novelty detection
  • Stream data management
  • Dynamic segmentation & clustering
  • Deep learning
  • Multimodal data linkage
  • Integration of multi-scale models
  • Mining of unstructured, spatio-temporal, streaming and multimedia data
  • Computational intelligence in large sensor networks
  • Predictive analytics and recommender systems
  • Real-time forecasting
  • Access on-demand in distributed databases
  • Affordable high performance computing
  • Privacy protecting data mining
  • Data integrity & provenance methods
  • Visualization methods

Information for authors

The submitted papers should present results of the original and unpublished research. The papers will be reviewed by the CYBCONF 2015 International Program Committee. Accepted papers will be presented at the conference and will be included in the conference proceedings. Papers must be prepared using IEEE templates for conference proceedings. All papers must be submitted electronically via conference submission system.

Important dates

Paper submission:  March 15, 2015
Notification of acceptance:  April 15, 2015
Final paper submission and Early registration:     April 30, 2015
Conference:  June 24-26, 2015


Adel M. Alimi, University of Sfax, Tunisia

Vaclav Snasel, VSB-Technical University of Ostrava, Czech Republic

Program committee

Ivan Zelinka, VSB-Technical University of Ostrava, Czech Republic
Michał Woźniak, Wrocław University of Technology, Wroclaw, Poland
Pavel Kromer, VSB-Technical University of Ostrava, Czech Republic
Jan Platos, VSB-Technical University of Ostrava, Czech Republic
Petr Gajdos, VSB-Technical University of Ostrava, Czech Republic
Miroslav Voznak, VSB-Technical University of Ostrava, Czech Republic
Guanrong Chen, City University of Hong Kong, China
Rössler Otto E., Institut für Physikalische und Theoretische Chemie, Tübingen, Germany
Adamatzky Andy, Unconventional Computing Centre, Bristol, UK
Lampinen Jouni, University of Vaasa, Finland
Suganthan Ponnuthurai Nagaratnam, Nanyang Technological University of Singapore
Lozi René, Laboratoire J.A. Dieudonné Université de Nice Sophia-Antipolis Nice, France
Chadli Mohammed, Université de Picardie Jules Verne, Amiens, France
Ajith Abraham, Machine Intelligence Research Labs (MIR Labs), USA
Petr Škoda, Astronomical Institute, Academy of Science, Czech Republic
Jaroslav Pokorný, Charles University, Prague, Czech Republic
Nizar Rokbani, University of Sousse, Tunisia
Habib M. Kammoun, University of Sfax, Tunisia
Tarek M. Hamdani, University of Tiba, KSA
Aboul Ella Hassanien, University of Cairo, Egypt
Farhi Marir, Zayed University, UAE