[hpc-announce] IEEE Big Data 2015: Call for Papers
Weijia Xu
xwj at tacc.utexas.edu
Fri May 8 10:03:15 CDT 2015
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ 2015 IEEE International Conference on Big Data (IEEE Big Data 2015)
+ Oct 29-Nov 1 2015, Santa Clara, CA, USA
+
+ http://cci.drexel.edu/bigdata/bigdata2015/
+
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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/, regular paper acceptance rate: 17.0%)
was held in Santa Clara , CA from Oct 6-9, 2013 with more than 400 registered participants from 40
countries. The IEEE Big Data 2014 (http://cci.drexel.edu/bigdata/bigdata2014/index.htm, regular paper
acceptance rate: 18.5.0%) was held in Washington DC, Oct 27-30, 2014 with more than 600 registered
participants from 45 countries. The 2015 IEEE International Conference on Big Data (IEEE Big Data 2015)
will continue the success of the previous IEEE Big Data conferences. 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
a. Novel Theoretical Models for Big Data
b. New Computational Models for Big Data
c. Data and Information Quality for Big Data
d. New Data Standards
2. Big Data Infrastructure
a. Cloud/Grid/Stream Computing for Big Data
b. High Performance/Parallel Computing Platforms for Big Data
c. Autonomic Computing and Cyber-infrastructure, System Architectures,
Design and Deployment
d. Energy-efficient Computing for Big Data
e. Programming Models and Environments for Cluster, Cloud, and Grid Computing
to Support Big Data
f. Software Techniques and Architectures in Cloud/Grid/Stream Computing
g. Big Data Open Platforms
h. New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
i. Software Systems to Support Big Data Computing
3. Big Data Management
a. Search and Mining of variety of data including scientific and engineering,
social, sensor/IoT/IoE, and multimedia data
b. Algorithms and Systems for Big Data Search
c. Distributed, and Peer-to-peer Search
d. Big Data Search Architectures, Scalability and Efficiency
e. Data Acquisition, Integration, Cleaning, and Best Practices
f. Visualization Analytics for Big Data
g. Computational Modeling and Data Integration
h. Large-scale Recommendation Systems and Social Media Systems
i. Cloud/Grid/Stream Data Mining- Big Velocity Data
j. Link and Graph Mining
k. Semantic-based Data Mining and Data Pre-processing
l. Mobility and Big Data
m. Multimedia and Multi-structured Data- Big Variety Data
4. Big Data Search and Mining
a. Social Web Search and Mining
b. Web Search
c. Algorithms and Systems for Big Data Search
d. Distributed, and Peer-to-peer Search
e. Big Data Search Architectures, Scalability and Efficiency
f. Data Acquisition, Integration, Cleaning, and Best Practices
g. Visualization Analytics for Big Data
h. Computational Modeling and Data Integration
i. Large-scale Recommendation Systems and Social Media Systems
j. Cloud/Grid/Stream Data Mining-Big Velocity Data
k. Link and Graph Mining
l. Semantic-based Data Mining and Data Pre-processing
m. Mobility and Big Data
n. Multimedia and Multi-structured Data- Big Variety Data
5. Big Data Security & Privacy
a. Intrusion Detection for Gigabit Networks
b. Anomaly and APT Detection in Very Large Scale Systems
c. High Performance Cryptography
d. Visualizing Large Scale Security Data
e. Threat Detection using Big Data Analytics
f. Privacy Threats of Big Data
g. Privacy Preserving Big Data Collection/Analytics
h. HCI Challenges for Big Data Security & Privacy
i. User Studies for any of the above
j. Sociological Aspects of Big Data Privacy
6. Big Data Applications
a. Complex Big Data Applications in Science, Engineering, Medicine,
Healthcare, Finance, Business, Law, Education, Transportation, Retailing,
Telecommunication
b. Big Data Analytics in Small Business Enterprises (SMEs),
c. Big Data Analytics in Government, Public Sector and Society in General
d. Real-life Case Studies of Value Creation through Big Data Analytics
e. Big Data as a Service
f. Big Data Industry Standards
g. Experiences with Big Data Project Deployments
===============================================================================
= Important Dates
===============================================================================
Electronic submission of full papers: July 1, 2015
Notification of paper acceptance: Sept 4, 2015
Camera-ready of accepted papers: Sept 25, 2015
Conference: Oct 29-Nov 1, 2015
===============================================================================
= 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 2015 will offer at least 25 student travel awards (the number
may be increased later if more sponsorship funds are obtained)to student authors
(including post-doc) (IEEE Big Data 2014 had 35 student travel awards; IEEE Big
Data 2013 had 17 student travel awards).
===============================================================================
= Conference Organizers
===============================================================================
BigData Steering Committee Chair:
Prof. Xiaohua Tony Hu, Drexel University, USA
Conference Co-Chairs:
Dr. Laura Hass, IBM Research Accelerated Discovery Lab, USA
Prof. Vipin Kumar, University of Minnesota, USA
Program Co-Chairs:
Dr. Howard Ho, IBM Amerdan Research Center, USA
Prof. Beng Chin Ooi, National University of Singapore, Singapore
Prof. Prof. Mohammed J. Zaki, Rensselaer Polytechnic Institute, USA
Industry and Government Program Committee Chair
Dr. Morris Hui-I Hsiao, Institute for Information Industry, Taiwan
Dr. Jian Li, Huawei Technologies Co. Ltd, USA
Dr. Sudarsan Rachuri, National Institute of Standard and Technology, USA
Dr. Shipeng Yu, LinkedIn, USA
===============================================================================
= Paper Submission Guidelines
===============================================================================
Please submit a full-length paper (up to 10 page IEEE 2-column format) through
the online submission system:
https://wi-lab.com/cyberchair/2015/bigdata15/scripts/submit.php?subarea=BigD
Papers should be formatted to IEEE Computer Society Proceedings Manuscript.
Formatting Guidelines (see link to "formatting instructions" below).
DOC version: ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.doc
PDF version: ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.pdf
LaTex Formatting Macros: ftp://pubftp.computer.org/Press/Outgoing/proceedings/IEEE_CS_Latex8.5x11x2.zip
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