BigData 2015 - 2015 IEEE International Conference on Big Data (IEEE Big Data 2015)
Date2015-10-29 - 2015-11-01
Deadline2015-07-01
VenueSanta Clara, CA, USA - United States
Keywords
Website
Topics/Call fo Papers
2015 IEEE International Conference on Big Data (IEEE Big Data 2015)
http://cci.drexel.edu/bigdata/bigdata2015/
Oct 29-Nov 1 2015, Santa Clara, CA, 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/ , 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.ht..., 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 andArchitectures 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 DataSearch
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/StreamData 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
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 ?35 student travel awards, IEEE Big Data 2013 ? 17 student travel awards)
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, Qatar Computing Research Institute, Qatar,
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
BigData Steering Committee Chair:
Prof. Xiaohua Tony Hu, Drexel University, USA, xh29-AT-drexel.edu
Paper Submission:
Please submit a full-length paper (upto 10 page IEEE 2-column format) through the online submission system.
https://wi-lab.com/cyberchair/2015/bigdata15/scrip...
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, 2015
Notification of paper acceptance: Sept 4, 2015
Camera-ready of accepted papers: Sept 25, 2015
Conference: October 29-Nov 1, 2015
To subscribe to this list, the user sends an email, with blank subject line, to listserv-AT-lists.drexel.edu . In the text box, the user types: subscribe BIGDATA.
To unsubscribe from a list, the user sends an email to listserv-AT-lists.drexel.edu with the message: signoff BIGDATA.
http://cci.drexel.edu/bigdata/bigdata2015/
Oct 29-Nov 1 2015, Santa Clara, CA, 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/ , 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.ht..., 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 andArchitectures 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 DataSearch
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/StreamData 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
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 ?35 student travel awards, IEEE Big Data 2013 ? 17 student travel awards)
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, Qatar Computing Research Institute, Qatar,
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
BigData Steering Committee Chair:
Prof. Xiaohua Tony Hu, Drexel University, USA, xh29-AT-drexel.edu
Paper Submission:
Please submit a full-length paper (upto 10 page IEEE 2-column format) through the online submission system.
https://wi-lab.com/cyberchair/2015/bigdata15/scrip...
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, 2015
Notification of paper acceptance: Sept 4, 2015
Camera-ready of accepted papers: Sept 25, 2015
Conference: October 29-Nov 1, 2015
To subscribe to this list, the user sends an email, with blank subject line, to listserv-AT-lists.drexel.edu . In the text box, the user types: subscribe BIGDATA.
To unsubscribe from a list, the user sends an email to listserv-AT-lists.drexel.edu with the message: signoff BIGDATA.
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Last modified: 2015-04-30 22:35:36