2014 IEEE International Conference on Big Data , October 27-30, 2014, Washington DC, USA.

Call for Papers

2014 IEEE International Conference on Big Data (IEEE BigData 2014)

http://cci.drexel.edu/bigdata/bigdata2014/index.htm

October 27-30, 2014, Washington DC, USA

In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately society itself. The IEEE Big Data has established itself as the top tier research conference in Big Data. The first conference IEEE Big Data 2013 ( http://cci.drexel.edu/bigdata/bigdata2013/ ) was held in Santa Clara , CA from Oct 6-7, 2013, 259 paper submissions for the main conference and 32 paper submissions for the industry and government program. Of those, 44 regular papers and 53 short papers were accepted, which translates into a selectivity that is on-par with top tier conferences. Also, there were 14 workshops associated with IEEE Big Data 2013 covering various important topics related to various aspects of Big Data research, development and applications, and more than 400 participants from 40 countries attend the 4-day event.

The IEEE International Conference on Big Data 2014(IEEE BigData 2014) continues the success of the IEEE BigData 2013. It will provide a leading forum for disseminating the latest research in Big Data Research, Development, and Applications.

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

  1. Big Data Science and Foundations
    1. Novel Theoretical Models for Big Data
    2. New Computational Models for Big Data
    3. Data and Information Quality for Big Data
    4. New Data Standards
  1. Big Data Infrastructure
    1. Cloud/Grid/Stream Computing for Big Data
    2. High Performance/Parallel Computing Platforms for Big Data
    3. Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
    4. Energy-efficient Computing for Big Data
    5. Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
    6. Software Techniques andArchitectures in Cloud/Grid/Stream Computing
    7. Big Data Open Platforms
    8. New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
    9. Software Systems to Support Big Data Computing
  1. Big Data Management
    1. Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data
    2. Algorithms and Systems for Big DataSearch
    3. Distributed, and Peer-to-peer Search
    4. Big Data Search Architectures, Scalability and Efficiency
    5. Data Acquisition, Integration, Cleaning, and Best Practices
    6. Visualization Analytics for Big Data
    7. Computational Modeling and Data Integration
    8. Large-scale Recommendation Systems and Social Media Systems
    9. Cloud/Grid/Stream Data Mining- Big Velocity Data
    10. Link and Graph Mining
    11. Semantic-based Data Mining and Data Pre-processing
    12. Mobility and Big Data
    13. Multimedia and Multi-structured Data- Big Variety Data
  1. Big Data Search and Mining
    1. Social Web Search and Mining
    2. Web Search
    3. Algorithms and Systems for Big Data Search
    4. Distributed, and Peer-to-peer Search
    5. Big Data Search Architectures, Scalability and Efficiency
    6. Data Acquisition, Integration, Cleaning, and Best Practices
    7. Visualization Analytics for Big Data
    8. Computational Modeling and Data Integration
    9. Large-scale Recommendation Systems and Social Media Systems
    10. Cloud/Grid/StreamData Mining- Big Velocity Data
    11. Link and Graph Mining
    12. Semantic-based Data Mining and Data Pre-processing
    13. Mobility and Big Data
    14. Multimedia and Multi-structured Data- Big Variety Data

 

  1. Big Data Security & Privacy
  2. Intrusion Detection for Gigabit Networks
  3. Anomaly and APT Detection in Very Large Scale Systems
  4. High Performance Cryptography
  5. Visualizing Large Scale Security Data
  6. Threat Detection using Big Data Analytics
  7. Privacy Threats of Big Data
  8. Privacy Preserving Big Data Collection/Analytics
  9. HCI Challenges for Big Data Security & Privacy
  10. User Studies for any of the above
  11. Sociological Aspects of Big Data Privacy
  1. Big Data Applications
    1. Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication
    2. Big Data Analytics in Small Business Enterprises (SMEs),
    3. Big Data Analytics in Government, Public Sector and Society in General
    4. Real-life Case Studies of Value Creation through Big Data Analytics
    5. Big Data as a Service
    6. Big Data Industry Standards
    7. Experiences with Big Data Project Deployments

 

INDUSTRIAL Track

The Industrial Track solicits papers describing implementations of Big Data solutions relevant to industrial settings. The focus of industry track is on papers that address the practical, applied, or pragmatic or new research challenge issues related to the use of Big Data in industry. We accept full papers (up to 10 pages) and extended abstracts (2-4 pages).

Student Travel Award

IEEE Big Data 2014 will offer as many student travel awards as possible to student authors (including post-doc)  (IEEE Big Data 2013 – 17 student travel awards)

Conference Co-Chairs:

Dr. Charu Aggarwal, IBM T.J Watson Research, USA
Prof. Nick Cercone, York University, Canada
Prof. Vasant Honavar, Penn State University, USA
Program Co-Chairs:

Prof. Jimmy Lin, University of Maryland, USA

Prof. Jian Pei, Simon Fraser University, Canada

Industry and Government Program Committee Chair

Mr. Wo Chang, National Institute of Standard and Technology, USA
Dr. Raghunath Nambiar, Cisco Systems Inc, USA

BigData Steering Committee Chair:

Prof. Xiaohua Tony Hu, Drexel University, USA, thu@cis.drexel.edu

Paper Submission:

Please submit a full-length paper (upto9 page IEEE 2-column format) through the online submission system.

http://wi-lab.com/cyberchair/2014/bigdata14/cbc_index.php

Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to “formatting instructions” below).

Formatting Instructions
8.5″ x 11″ (DOC, PDF)
LaTex Formatting Macros

Important Dates:

Electronic submission of full papers: July 1, 2014

Notification of paper acceptance: Sept 1, 2014

Camera-ready of accepted papers: Sept 25, 2014

Conference: October 27-30, 2014

 

 

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