Special Sessions

SS27: Machine Learning for Big Data Analytics

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Big data analytics has emerged as a promising and exciting area of research owing to data explosion in all domains during the past few decades. Nowadays, data is witnessing unmatched momentum with respect to each area of research and industry. In such scenario of rapid data explosion, conventional data analytical techniques fail to give optimized performance despite its potential to handle large amount of data. Hence, rigorous research is taking place to establish various techniques, methodologies and algorithms to address the issue in an efficient manner. Among several approaches, machine learning approach has gained an unparalleled acceptance along a broad spectrum. This has advocated widespread employment of machine learning in applications related to big data analytics.

This special session is entirely based on the current research trends in the domain of machine learning in big data analytics. The prime focus of this special session is to bring academicians, researchers and practitioners together at one platform and discuss the current research trends in this domain.

Topics of interest:

We invite original (un-published) research contributions based on the above mentioned theme including following topics but not limited to:

  • Data Analytics and Machine Learning models
  • Issues and Challenges in Data Analytics
  • Deep and reinforcement learning
  • Big Data analytics for various applications
  • Hybrid Fusion Systems
  • Data acquisition/analysis/mining
  • Knowledge representation and reasoning
  • Data processing and optimization methods
  • Data Analytics for Covid-19
  • Modeling, simulation, and optimization
  • Intelligent Security Systems
  • Fusion control systems developments
  • Organization Based Management system.

  • Organizers

    Dr. Nonita Sharma, NIT, Jalandhar, India.
    Dr. Monika Mangla, LTCoE, Koparkhairane, Navi Mumbai, India.
    Dr. Thirunavukkarasu K, Galgotia University, Noida, India.

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