Streaming Data Analytics and Applications Minitrack

In stream data analytics data are analyzed online as they arrive and decisions are made in real- time. This minitrack aims to present and share new research in defining and highlighting the values of stream data analytics, including new theory, algorithms, innovation in methodologies, and benefits from a variety of applications.

Topics include, but are not constrained only to:

  • Data stream mining techniques and methodologies
  • Distributed data stream models
  • Concept drift in streaming data
  • Data streams visualization
  • Real-world applications using streaming data analytics in:
    • Social networks
    • Intelligence and cybersecurity
    • Smart power grid
    • Sensor networks
    • Internet of Things

Minitrack Co-Chairs:

Mehmed Kantardzic (Primary Contact)
University of Louisville

Jozef Zurada
University of Louisville

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