Foundations of Data Mining & Machine Learning

• Theoretical foundations, algorithms, and models
• Optimization for data mining
• Scalable, distributed, and parallel learning
• Online, incremental, and streaming learning
• Self supervised, weakly supervised, and semi supervised learning
• Causal discovery and causal data mining
• Explainable and interpretable data mining
Advanced Data Mining Techniques

• Mining structured, semi structured, and unstructured data
• Text, graph, web, multimedia, and social data mining
• Spatio temporal, mobility, and sensor data mining
• High dimensional, sparse, and heterogeneous data
• Personalization, recommendation, and user modeling
• Visualization, summarization, and pattern discovery
Big Data Systems, Platforms & Scalability

• Large scale data mining systems and architectures
• Distributed, cloud, and edge data processing
• Analytical data platforms, data lakes, and lakehouses
• High performance data management and query processing
• Data mining on GPUs, accelerators, and specialized hardware
Databases: Theory, Systems & Architectures

• Database management systems (DBMS)
• Query processing, optimization, and indexing
• Transaction management and concurrency control
• Very large databases (VLDB)
• Multi model and next generation database systems
• Temporal, spatial, and high dimensional databases
• Metadata management and schema evolution
Data Integration, Quality & Governance

• Data integration, fusion, and interoperability
• Data cleaning, quality assessment, and error detection
• Entity resolution and deduplication
• Data semantics, ontologies, and knowledge representation
• Data lineage, provenance, and governance frameworks
Privacy, Security & Trust in Data Systems

• Privacy preserving data mining
• Differential privacy and secure computation
• Data anonymization and synthetic data
• Trust, security, and risk management in digital ecosystems
• Secure data sharing and federated data management
Knowledge Discovery, Reasoning & Decision Support

• Knowledge graphs and semantic data processing
• Knowledge modeling and reasoning
• Intelligent decision support systems
• Automated discovery pipelines and data driven decision systems
Data Streams, Real Time Analytics & Edge Intelligence

• Stream processing and real time analytics
• Event detection, anomaly detection, and time series mining
• Edge data management and IoT analytics
• Mobile and pervasive data intelligence
Information Retrieval, Search & Web Data

• Information retrieval models and systems
• Web mining, search engines, and ranking algorithms
• Semantic web and linked data
• Large scale content management
Applied Data Mining & Domain Driven Analytics

• Data mining for finance, e commerce, and digital business
• Healthcare, biomedical, and scientific data mining
• Industrial analytics, automation, and process mining
• Smart cities, transportation, and environmental analytics
Data Driven Systems, Workflows & Automation

• Data pipelines, workflow automation, and orchestration
• Process modeling, monitoring, and optimization
• MLOps and automated data engineering
• Human in the loop analytics
Emerging Topics in Data Mining & Databases

• Graph neural networks (GNNs)
• Foundation models for data management
• Data centric AI
• Responsible and ethical data mining
• Synthetic data generation and evaluation
• Multimodal data integration and analytics

Hard copy of the proceedings will be distributed during the Conference. The softcopy will be available on AIRCC digital library.