14th International Conference on Database , Data Mining and Artificial Intelligence (DBDM 2026)

14th International Conference on Database , Data Mining and Artificial Intelligence (DBDM 2026) March 21 ~ 22, 2026, Sydney, Australia https://www.ccnet2026.org/dbdm/index Scope & Topics 14th International Conference on Database , Data Mining and Artificial Intelligence (DBDM 2026) provides a premier forum for researchers, practitioners, and industry experts to present and discuss the latest innovations, trends, results, and challenges across databases, data mining, and AI driven intelligent systems. The conference aims to foster collaboration and knowledge exchange through high quality, peer reviewed research contributions. DBDM 2026 encourages submissions in all areas related to databases, data mining, machine learning, and AI driven intelligent systems. Topics include, but are not limited to: Topics of interest include, but are not limited to, the following: • Cloud, Distributed, and Parallel Databases • Big Data Platforms and Data Lake Architectures • Quer... Read more

14th International Conference on Database , Data Mining and Artificial Intelligence (DBDM 2026) March 21 ~ 22, 2026, Sydney, Australia https://www.ccnet2026.org/dbdm/index Scope & Topics 14th International Conference on Database , Data Mining and Artificial Intelligence (DBDM 2026) provides a premier forum for researchers, practitioners, and industry experts to present and discuss the latest innovations, trends, results, and challenges across databases, data mining, and AI driven intelligent systems. The conference aims to foster collaboration and knowledge exchange through high quality, peer reviewed research contributions. DBDM 2026 encourages submissions in all areas related to databases, data mining, machine learning, and AI driven intelligent systems. Topics include, but are not limited to: Topics of interest include, but are not limited to, the following: • Cloud, Distributed, and Parallel Databases • Big Data Platforms and Data Lake Architectures • Query Processing, Optimization, and Indexing • Transaction Processing and Concurrency Control • Data Cleaning, Integration, and Preparation • Data Quality, Provenance, and Governance • High Dimensional, Temporal, and Spatial Databases • Multi Model Databases (Graph, Document, Key Value, Time Series) • Data Streams and Real Time Data Management • Federated and Heterogeneous Databases • Storage Engines, Column Stores, and Log Structured Systems • Metadata, Schema, and Catalog Management • Data Mining Foundations and Algorithms • Deep Learning for Data Mining and Pattern Discovery • Graph Mining, Network Analysis, and Knowledge Graphs • Anomaly, Fraud, and Outlier Detection • Feature Engineering, Representation Learning, and Embeddings • Scalable and Distributed Data Mining • AutoML and Automated Knowledge Discovery • Data Warehousing, OLAP, and Analytical Processing • Data Mining Applications (Healthcare, Finance, IoT, Cybersecurity, etc.) • Explainable Data Mining and Responsible AI • AI for Big Data Analytics • Foundation Models and Large Scale Pretrained Models • Generative AI for Data Mining and Databases • AI Driven Query Optimization and Self Tuning Databases • Intelligent Information Systems • Multi Agent Systems and Intelligent Decision Support • Expert Systems and Knowledge Based Systems • Reinforcement Learning for Data Management • Human AI Interaction and Interactive AI • AI for Data Privacy, Security, and Trust • Data Science Workflows and Pipelines • Data Engineering for AI Systems • Edge, Fog, and IoT Data Management • Blockchain Data Management and Analytics • Smart Cities, Smart Grids, and Sensor Data Systems • Web, Social Media, and Multimedia Data Mining • Semantic Web, Ontologies, and Knowledge Representation • E Commerce, E Government, and Digital Business Analytics • Privacy Preserving Data Mining (PPDM) • Secure Data Sharing and Federated Learning • Adversarial Machine Learning • Ethical AI, Fairness, and Bias Mitigation • Trust, Privacy, and Security in Digital Business • Compliance, Governance, and Responsible Data Use Paper Submission Authors are invited to submit papers through the conference Submission System by February 21, 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 in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from DBDM 2026, after further revisions, will be published in the special issues of the following journals • International Journal of Database Management Systems (IJDMS) • International Journal of Data Mining & Knowledge Management Process ( IJDKP) • International Journal of Web & Semantic Technology (IJWesT) - IS Indexed • Information Technology in Industry (ITII) Important Dates Third Batch : (Submissions after January 31, 2026) • Submission Deadline : February 21, 2026 • Authors Notification : March 07, 2026 • Registration & Camera-Ready Paper Due : March 14, 2026 Contact Us Here's where you can reach us : dbdm@ccnet2026.org or confdbdm@gmail.com Submission Url https://www.ccnet2026.org/submission/index.php