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DMDB 2026 : 13th International Conference on Data Mining and Database

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Link: https://ccseit2026.org/dmdb/index
 
When Mar 14, 2026 - Mar 15, 2026
Where Vienna, Austria
Submission Deadline Jan 10, 2026
Notification Due Jan 24, 2026
Final Version Due Jan 31, 2026
Categories    data mining   databases   big data   data science
 

Call For Papers

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) 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 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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