2nd International Conference on Soft Computing, Data mining and Data Science (SCDD 2024)

Topics

• Data Mining
  • Knowledge Processing
  • Data Mining Applications
  • Data mining in medical informatics
  • Classification, Regression, Clustering & Association rules
  • Disaster prediction and management
  • Dimensionality reduction
  • Enterprise and business data management
  • Educational data mining
  • Feature selection and data cleansing
• Soft Computing
  • Bio-inspired Computing
  • Artificial immune systems
  • Data Visualization
  • Biomedical Engineering
  • E-commerce, e-medicine
  • Deep learning
  • Fuzzy Systems
  • Evolutionary Computing
  • Hybrid intelligent systems
  • Genetic algorithms
  • Morphic Computing
  • Machine learning
  • Nano & Micro-systems
  • Multi-agent System
  • Neural Networks
  • Nature-inspired computing
  • Probabilistic Reasoning
  • Pattern recognition
  • Rough , Soft Set Theory
  • Reactive Distributed AI
  • Software agents
  • Signal, Image processing
  • Swarm intelligence
  • Support vector machines
  • Vision Recognition
  • Telecommunications
  • Wavelet
• Data Science
  • Large-scale data mining
  • Information retrieval
  • Statistics for intelligent data analysis
  • Outlier analysis
  • Big Data Fundamentals and Applications Internet of Things (IoT)
  • Visual data mining
  • Big Data Search
  • Big Data Management and Frameworks
  • Consistent Data Model
  • Big Data security
  • Data Streams Mining, Graph Database & Mining, Spatial Data Mining
  • Data and Knowledge Representation
  • Exploring Data Analysis
  • Databases & Financial Modelling
  • Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge
  • Forecasting, Classification, Clustering
  • Integrating Constraints and Knowledge in the KDD Process
  • Infrastructures for Big Data
  • Interactive Data Exploration / Visualization and Discovery
  • Integration of Data Warehousing
  • Languages and Interfaces for Data Mining
  • Knowledge Discovery Framework and Process, Including Pre- and Post-Processing
  • Learning Problems
  • Learning in knowledge-intensive systems
  • Mining from Low-Quality Information Sources
  • Machine Learning Applications
  • OLAP and Data Mining
  • Mining Trends, Opportunities and Risks
  • Parallel and Distributed Data Mining Algorithms
  • Operations Research
  • Security and Information Hiding in Data Mining
  • Pre-Processing Techniques, Visualization
  • Statistical Techniques for Generation a Robust
  • Social Networks, Educational Data Mining
  • Text video, Multimedia Data Mining, Web Mining