The 2021 3rd International Conference on Big Data Engineering (BDE 2021) will be held during May 29-31, 2021 in Shanghai, China. BDE 2021 is an international forum for sharing knowledge and results in theory, methodology and new advances and research results in the fields of Big Data Engineering. The conference will bring together researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. The Conference welcomes significant contributions in all major fields of the Big Data Engineering in theoretical and practical aspects. It will put special emphasis on the participations of PhD students, Postdoctoral fellows and other young researchers from all over the world. It would be beneficial to bring together a group of experts from diverse fields to discuss recent progress and to share ideas on open questions. The conference will feature world-class keynote speakers in the main areas.
Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Such datasets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). More importantly, big data has to be of high value (Value) and establish trust in it for business decision making (Veracity). Various technologies are being discussed to support the handling of big data such as massively parallel processing databases, scalable storage systems, cloud computing platforms, and MapReduce.
The BDE 2021 organized by the ACM Singapore Chapter will present the most recent and exciting advances in Big Data Engineering through keynote talks. Prospective authors are invited to submit papers on relevant algorithms and applications including, but not limited to:
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 and Architectures 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
