(Including but not limited to the following topics)
Track 1: Big Data Mining
Big Data Theory and Algorithms
Big Data Storage and Management
Big Data Mining and Analysis
Distributed and Parallel Computing
Real-time Data Stream Processing
Data Cleaning and Preprocessing
Multi-source Data Fusion
Data Visualization and Analysis
Big Data Security and Privacy Protection
Cloud Computing and Big Data
Edge Computing for Big Data
Knowledge Graphs and Big Data
High-Performance Computing for Big Data
Data-Driven Decision Support Systems
Big Data Industry Applications
Track 2: Distributed Computing
Optimization of Big Data Computing Frameworks (Hadoop, Spark, Flink, Storm)
Stream Data Processing, Real-time Computing and Message Middleware (Kafka, Pulsar)
Distributed Storage Systems (HDFS, Ceph, MinIO) and Data Lakes
Distributed Databases (NewSQL, NoSQL, Graph Databases) and Data Warehouses
Memory Computing, New Hardware Acceleration (FPGA, GPU) Data Processing
Distributed Scheduling, Load Balancing and Resource Management (YARN, Kubernetes)
High-Performance Data Query and Index Optimization
Distributed Computing Applications in Machine Learning, Graph Computing, etc.
Track 3: Internet of Things
Artificial Intelligence Technologies and Applications
CPS Technologies and Intelligent Information Systems
Multi-network Resource Sharing in the IoT Environment
Internet of Things Technology Architecture
Cloud Computing and Big Data in the IoT
Edge Intelligence and Blockchain Smart City
Internet of Things wearable devices
Smart home
Internet of Things and sensor technology, etc. ......