Martes, 28 Febrero 2017 14:33

IEEE Big Data 2017 Call for Papers

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Los invitamos a participar en el Call for papers de la IEEE Big Data 2017, que se realizará del 11 al 14 de diciembre del 2017 en Boston, MA, USA.

 

In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately our society itself. The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data.

The 2017 IEEE International Conference on Big Data (IEEE Big Data 2017) will continue the success of the previous IEEE Big Data conferences. It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications.

We solicit high-quality original research papers (and significant work-in-progress papers) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity), including the Big Data challenges in scientific and engineering, social, sensor/IoT/IoE, and multimedia (audio, video, image, etc.) big data systems and applications. Example topics of interest includes but is not limited to the following:

Big Data Science and Foundations

  • Novel Theoretical Models for Big Data
  • New Computational Models for Big Data
  • Data and Information Quality for Big Data
  • New Data Standards

 Big Data Infrastructure

  • Cloud/Grid/Stream Computing for Big Data
  • High Performance/Parallel Computing Platforms for Big Data
  • Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
  • Energy-efficient Computing for Big Data
  • Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
  • Software Techniques andArchitectures in Cloud/Grid/Stream Computing
  • Big Data Open Platforms
  • New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
  • Software Systems to Support Big Data Computing

Big Data Management

  • Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data
  • Algorithms and Systems for Big Data Search
  • Distributed, and Peer-to-peer Search
  • Big Data Search Architectures, Scalability and Efficiency
  • Data Acquisition, Integration, Cleaning, and Best Practices
  • Visualization Analytics for Big Data
  • Computational Modeling and Data Integration
  • Large-scale Recommendation Systems and Social Media Systems
  • Cloud/Grid/Stream Data Mining- Big Velocity Data
    Link and Graph Mining
  • Semantic-based Data Mining and Data Pre-processing
  • Mobility and Big Data
  • Multimedia and Multi-structured Data- Big Variety Data

Big Data Search and Mining

  • Big Data Search and Mining
  • Social Web Search and Mining
  • Web Search
  • Algorithms and Systems for Big Data Search
  • Distributed, and Peer-to-peer Search
  • Big Data Search Architectures, Scalability and Efficiency
  • Data Acquisition, Integration, Cleaning, and Best Practices
  • Visualization Analytics for Big Data
  • Computational Modeling and Data Integration
  • Large-scale Recommendation Systems and Social Media Systems
  • Cloud/Grid/StreamData Mining- Big Velocity Data
  • Link and Graph Mining
  • Semantic-based Data Mining and Data Pre-processing
  • Mobility and Big Data
  • Multimedia and Multi-structured Data-Big Variety Data

Big Data Security, Privacy and Trust

  • Intrusion Detection for Gigabit Networks
  • Anomaly and APT Detection in Very Large Scale Systems
  • High Performance Cryptography
  • Visualizing Large Scale Security Data
  • Threat Detection using Big Data Analytics
  • Privacy Threats of Big Data
  • Privacy Preserving Big Data Collection/Analytics
  • HCI Challenges for Big Data Security & Privacy
  • User Studies for any of the above
  • Sociological Aspects of Big Data Privacy
  • Trust management in IoT and other Big Data Systems

Big Data Applications

  • Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication
  • Big Data Analytics in Small Business Enterprises (SMEs)
  • Big Data Analytics in Government, Public Sector and Society in General
  • Real-life Case Studies of Value Creation through Big Data Analytics
  • Big Data as a Service
  • Big Data Industry Standards
  • Experiences with Big Data Project Deployments

Important Dates:

  • Aug. 7, 2017: Electronic submission of full papers
  • Oct. 9, 2017: Notification of paper acceptance
  • Nov. 10, 2017: Camera-ready of accepted papers
  • Dec. 11-14, 2017: Conference

Consulte más información AQUÍ

IEEE Big Data 2017 will offer student travel to student authors (including post-docs)

Información adicional

  • Fecha inicio Conferencia: Lunes, 11 Diciembre 2017
  • Fecha fin conferencia: Jueves, 14 Diciembre 2017
  • Lugar conferencia: Boston, MA, USA
Leído 4729 Tiempo Última modificación Martes, 28 Febrero 2017 15:09