posted by organizer: zbking || 26289 views || tracked by 71 users: [display]

IEEE BigData 2015 : 2015 IEEE International Conference on Big Data

FacebookTwitterLinkedInGoogle

Link: http://cci.drexel.edu/bigdata/bigdata2015/
 
When Oct 29, 2015 - Nov 1, 2015
Where Santa Clara, CA, USA
Submission Deadline Jul 1, 2015
Notification Due Sep 4, 2015
Final Version Due Sep 25, 2015
Categories    big data   data management   data search and mining   data applications
 

Call For Papers

Call for 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.htm, regular paper acceptance rate: 18.50%) 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 as many student travel awards as possible 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. Mahammed J. Zaki, Rensselaer Polytechnic Institute, USA

Industry and Government Program Committee Chair
Dr. Morris Hui-I Hsiao, Institute for Information Industry, Taiwan Raghunath Nambiar,
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, thu@cis.drexel.edu

Paper Submission:
Please submit a full-length paper (upto9 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).

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

Important Dates:
Electronic submission of full papers: July 12, 2015
Notification of paper acceptance: Sept 4, 2015
Camera-ready of accepted papers: Sept 25, 2015
Conference: October 29-Nov 1, 2015

Related Resources

IEEE BDAI 2025   IEEE--2025 the 8th International Conference on Big Data and Artificial Intelligence (BDAI 2025)
ICoSR 2025   2025 4th International Conference on Service Robotics
IEEE AMCAI 2025   IEEE Afro-Mediterranean Conference on Artificial Intelligence
BIBC 2024   5th International Conference on Big Data, IOT and Blockchain
BDAI 2025   IEEE--2025 the 8th International Conference on Big Data and Artificial Intelligence (BDAI 2025)
PAKDD 2025   29th Pacific-Asia Conference on Knowledge Discovery and Data Mining
IEEE-EI/Scopus-IECA 2025   2025 2nd International Conference on Informatics Education and Computer Technology Applications -IEEE Xplore/EI/Scopus
EEI 2024   10th International Conference on Emerging Trends in Electrical, Electronics & Instrumentation Engineering
SPIE-Ei/Scopus-CMLDS 2025   2025 2nd International Conference on Computing, Machine Learning and Data Science (CMLDS 2025) -EI Compendex & Scopus
FRUCT37   The 37th IEEE FRUCT Conference