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 first conference IEEE Big Data 2013 had more than 400 registered participants from 40 countries.
(Big Data 2013 The regular paper acceptance rate: 17.0%)
The IEEE Big Data 2015 had more than 780 registered participants from 49 countries.
( Big Data 2015 The regular paper acceptance rate: 16.8%)
The 2016 IEEE International Conference on Big Data (IEEE Big Data 2016) 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
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
12月05日
2016
12月08日
2016
注册截止日期
2022年12月13日 日本 Kyoto
2022 IEEE International Conference on Big Data2021年12月15日 美国 Orlando
2021 IEEE International Conference on Big Data2018年12月10日 美国
2018 IEEE International Conference on Big Data2017年12月11日 美国 Boston,USA
2017 IEEE International Conference on Big Data2015年10月29日 美国
2015年IEEE大数据国际会议2014年10月27日 美国
2014年IEEE大数据国际会议2013年10月06日 美国
2013 IEEE国际大数据会议
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