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

Website https://ccseit2026.org/dmdb/index | Edit Freely

Category Data Mining; Database Management Systems; Digital Libraries

Deadline: February 14, 2026 | Date: March 14, 2026

Venue/Country: Vienna, Austria, Austria

Updated: 2026-02-09 16:12:10 (GMT+9)

Call For Papers - CFP

March 14 ~ 15, 2026, Vienna, Austria

https://ccseit2026.org/dmdb/index

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 February 14, 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 Computer Science Conference Proceedings (H index 45) 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

Second Batch: Submissions after February 08, 2026

Submission Deadline: February 14, 2026

Authors Notification : March 03, 2026

Registration & Camera-Ready Paper Due : March 07, 2026

Contact Us

Here’s where you can reach us: dmdbccseit2026.org (or) dmdbconfeyahoo.com

Paper Submission Link: https://ccseit2026.org/submission/index.php