13th International Conference on Data Mining and Database (DMDB 2026)
March 14~ 15, 2026, Vienna, Austria Scope & Topics 13th International Conference on Data Mining and Database (DMDB 2026) will provide a forum for researchers who address this issue and to present their work in a peer-reviewed forum. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Data mining and Applications.
Authors are solicited to contribute to the Conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to. Topics of interest include, but are not limited to, the following 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
Paper Submission Authors are invited to submit papers through the conference Submission System by January 10, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from DMDB 2026, after further revisions, will be published in the special issue of the following journals. Important Dates | Submission Deadline | : | January 10, 2026 | | Authors Notification | : | January 24, 2026 | | Final Manuscript Due | : | January 31, 2026 |
Co - Located Event ***** The invited talk proposals can be submitted to dmdb@ccseit2026.org
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