Massive Dataflow analysis 

The first International Symposium on Data Science and Computational Intelligence 
                                                              DSCI 2017
                                                     in conjunction with


The 14th ACS/IEEE International Conference on Computer Systems and Applications

                                                           AICCSA 2017 
                 October 30th to November 3rd, 2017. Hammamet, Tunisia



The aim of The first International Symposium on Data Science and Computational Intelligence (DSCI 2017) is to bring together researchers and practitioners from different disciplines (statistics, automated learning, database, optimization, etc.) to discuss the different challenges in the field of Massive structured and unstructured data flow/stored analysis and to enable speakers to present their latest advances in this area. Submitted papers should be in accordance with IEEE format, and will be reviewed by at least two expert reviewers in terms of relevance, originality, contribution, correctness, and presentation. 

Proceedings of the workshops will be published by the IEEE Conference Publishing Services (CPS) and will be submitted for inclusion in the IEEE-Xplore and the IEEE Computer Society (CSDL) digital libraries.


 Topics of interest :

Authors are encouraged to submit their original work, which is not submitted elsewhere, to this workshop. The topics of DSCI17 are grouped in three tracks (but are not limited to):


  1. Data flow analysis

  • Data flows analysis methods 

  •   Social network flows analysis

  •  Multiple views and multi-views for data flow

  •   Heterogeneous sources flows process

  •   Bio-inspired methods for processing data streams

  • Multimedia streaming

      2. Data mining

  •  Extraction of sequential patterns in data

  •  Clustering and classifying data

  • Class change detection

  • Outliers detection and processing

  •  Feature evolving

      3.Computational Intelligence

  • Foundations of Computational Intelligence

  • Machine Learning

  •  Deep learning

  • Reinforcement Learning

  •  Swarm Intelligence

  • ·Ubiquitous Computing

  • Data storage and prototyping