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ICBDR 2021 : The 5th International Conference on Big Data Research

Tokyo, Japan
Event Date: Sep 25, 2021 - Sep 27, 2021
Submission Deadline: Apr 20, 2021
Notification of Acceptance: May 10, 2021
Camera Ready Version Due : May 30, 2021

About

Big data research is now well established as very diverse and pluri-disciplinary research area whose objective is to deal with massive and heterogeneous datasets and that are too large to be manipulated by conventional modelling and most current computational approaches. Clearly, big data challenges should require novel approaches and success stories should be shared, this favoring exchanges, cross-fertilization and finally advances as well as futur research directions to consider.

Call For Paper

We encourage original submissions related to, but not limited to, the following advanced energy materials based system topics:

Big Data Models and Algorithms

  • Foundational Models for Big Data
  • Algorithms and Programming Techniques for Big Data Processing
  • Big Data Analytics and Metrics
  • Representation Formats for Multimedia Big Data

Big Data Architectures

  • Cloud Computing Techniques for Big Data
  • Big Data as a Service
  • Big Data Open Platforms
  • Big Data in Mobile and Pervasive Computing

Big Data Management

  • Big Data Persistence and Preservation
  • Big Data Quality and Provenance Control
  • Big Data Storage and Retrieval

Big Data Security and Privacy

  • Big Data System Security and Integrity
  • Big Data Information Security
  • Privacy Preserving Big Data Analytics
  • Usable Security and Privacy for Big Data

Big Data in Smart Cities

  • Big Data for Improving Resilient Infrastructures
  • Big Data Applications such as Healthcare and Transportation
  • Big Data for Enterprise, Government, and Society
  • Big Data for Science and Engineering Research

Big Data Search, Mining, and Visualization

  • Algorithms and Systems for Big Data Search
  • Distributed, and Peer-to-peer Search
  • Machine learning based on Big Data
  • Visualization Analytics for Big Data

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