13^th International Conference on Data Mining and Database (DMDB 2026)

March 14~ 15, 2026, Vienna, Austria

Scope & Topics

13^th International Conference on Data Mining and Database (DMDB 2026) provides a premier platform for researchers, practitioners, and industry experts to share cutting edge developments in data mining, database systems, and data driven intelligence. The conference offers a rigorous, peer reviewed venue for presenting innovative research, real world applications, system implementations, and comprehensive survey studies.

We invite authors to submit high quality papers show casing significant advances in data mining, data analytics, and database management systems. Submissions may include original research results, novel methodologies, practical case studies, experimental evaluations, and industrial experiences that push the boundaries of data driven technologies and applications.

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 17, 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.

• International Journal of Database Management Systems (IJDMS)
  
• International Journal of Data Mining & Knowledge Management Process (IJDKP)
  
• Information Technology in Industry(ITII)
  

Important Dates

Co - Located Event

• 19^thInternational Conference on Network Security & Applications (CNSA 2026)
  
• 13^th International Conference on Artificial Intelligence and Applications (AIAP 2026)
  
• 16^th International Conference on Computer Science, Engineering and Information Technology(CCSEIT 2026)
  
• 13^th International Conference on Bioinformatics and Bioscience (ICBB 2026)
  
• 15^th International Conference on Information Theory (IT 2026)
  
• 7^th International Conference on Natural Language Processing, Information Retrieval and AI (NIAI 2026)
  
• 7^th International Conference on Signal Processing and Machine Learning (SIGML 2026)
  
• 7^th International Conference on Cloud and Internet of Things (ICCIoT 2026)
  
• 15^th International Conference on Mobile & Wireless Networks (MoWiN 2026)
  

***** The invited talk proposals can be submitted to dmdb@ccseit2026.org