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会议全称：IEEE International Conference on Big Data
录用率：NA
CCF分级：交叉/综合/新兴C
截稿时间：2024/9/3
录用通知时间：2024/10/27
官网链接：IEEE BigData 2024
征稿范围：
Example topics of interest includes but is not limited to the following:
1.
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
2. 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
3. Big Data Management Data
Acquisition, Integration, Cleaning, and Best Practices Computational
Modeling and Data Integration Large-scale Recommendation Systems and
Social Media Systems Cloud/Grid/Stream Data Mining- Big Velocity Data
Mobility and Big Data Multimedia and Multi-structured Data- Big Variety
Data Compliance and Governance for Big Data
4.
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 Link
and Graph Mining Semantic-based Data Mining and Data Pre-processing
Search and Mining of variety of data including scientific and
engineering, social, sensor/IoT/IoE, and multimedia data
5.
Big Data Learning and Analytics Predictive analytics on Big Data
Machine learning algorithms for Big Data Deep learning for Big Data
Feature representation learning for Big Data Dimension redution for Big
Data Physics informed Big Data learning Visualization Analytics for Big
Data
6. Data Ecosystem Data ecosystem
concepts, theory, structure, and process Ecosystem services and
management Methods for data exchange, monetization, and pricing Trust,
resilience, privacy, and security issues Privacy preserving Big Data
collection/analytics Trust management in Big Data systems Ecosystem
assessment, valuation, and sustainability Experimental studies of
fairness, diversity, accountability, and transparency
7.
Foundation Models for Big Data Big data management for pre-training Big
data management for fine-tuning Big data management for prompt-tuning
Prompt Engineering and its Management Foundation Model
Operationalization for multiple users
8. 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
