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Introduction

Data driven knowledge discovery and computational intelligence extraction have gained attention of scientific and business community over the last decade. This type of computational paradigm aims to gain pattern of knowledge and understand the knowledge hidden behind the abundant enormous data. Therefore, it is becoming increasingly important in the variety fields including social, service, Internet of Things, sensor networks, telecommunications, biology, and healthcare. A large number of research and applications have been theoretically and empirically focused. However, there are many associated scientific challenges, ranging from data capture, creation, storage, search, sharing, modeling, analysis, and visualization. The 2019 Data Science and Computational Intelligence (DSCI-2019) will devote to the data science and computational intelligence methods addressing the relevant scientific challenges on classification, prediction, clustering, statistics and optimization problems and their applications to both small and big data sets.

DSCI-2019 will provide a high-profile, leading-edge forum for researchers, engineers, and practitioners to present state-of-art advances and innovations in theoretical foundations, systems, infrastructure, tools, testbeds, and applications for the DSCI, as well as to identify emerging research topics and define the future.

Prospective authors are invited to submit their papers to DSCI-2019. All accepted papers are expected to be included in IEEE Xplore and will be indexed by Engineering Index (EI). The authors of selected best papers will be invited post conference to extend their contributions for special issues of prestigious journals to be planned in conjunction with the conference.

Track 1: Data Science Theory, Algorithms and Architectures
  • Foundations of Data Science
  • Programming Techniques
  • Analytics and Metrics
  • Representation Formats
  • Cloud Computing Techniques
  • Mobile and Pervasive Computing
  • Data Management
  • Data Quality
  • Social Computing
  • Social Network Analysis
  • Protection, Integrity and Privacy
  • Distributed Data Mining
  • Visualization
Track 2: Data Science Applications
  • Web Intelligence
  • Humanities
  • Stock Market Analysis
  • Scalable Cloud Data Management
  • Privacy and Security
  • Geosciences
  • Manufacturing and Supply Chains
  • Earth Science
  • Biomedical Informatics
  • High dimensional data
  • Social Networks
  • B2B Marketing and Sales
  • Healthcare
  • Sustainable development
  • Advanced Manufacturing
Track 3: Computational Intelligence for Big Data Processing
  • Artificial Neural Networks and Learning methods
  • Deep Learning
  • Knowledge based systems
  • Uncertainty management
  • Global optimization methods
  • Intelligent Control Systems
  • Intelligent Internet Systems
  • Intelligent Software Systems
  • Parallel Computation
  • Pattern Recognition
  • Systems Modelling
  • Web Mining
Track 4: Data Mining and Applications
  • Parallel and distributed data mining algorithms
  • Data streams mining
  • Time-series data mining
  • Graph mining
  • Spatial data mining
  • Text video, multimedia data mining
  • Web mining
  • Pre-processing techniques
  • Visualization
  • Security and information hiding in data mining
  • Data mining applications

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