15th International Conference on Data Mining & Knowledge Management Process (CDKP 2026)

 

The 15th International Conference on Data Mining & Knowledge Management Process (CDKP 2026) serves as a premier forum for researchers, practitioners, and industry experts to explore the evolving landscape of data driven discovery and intelligent knowledge management. As data continues to grow in scale, complexity, and strategic importance, the need for innovative methods to extract meaningful insights and support informed decision making has never been greater. CDKP 2026 brings together a global community of scholars to address these challenges and to share cutting edge advancements shaping the future of the field.

 

 

The conference provides a rigorous, peer reviewed platform for presenting original research, real world applications, case studies, and survey contributions that advance the state of the art in data mining and knowledge management. Authors are invited to submit high quality articles that highlight significant results, novel methodologies, emerging trends, and practical experiences across a wide range of related domains. Submissions may address, but are not limited to, the following areas:

 

 

·         Theoretical Foundations of Data Mining

·         Statistical Learning, Probabilistic Modeling and Causal Inference

·         Pattern Discovery, Frequent Itemsets and Association Rules

·         Data and Knowledge Representation

·         Automated Knowledge Discovery Pipelines and Frameworks

 

 

·         Supervised, Unsupervised and Semi Supervised Learning

·         Deep Learning Architectures and Optimization

·         Foundation Models and Generative AI (LLMs, Diffusion Models, Multimodal Models)

·         Representation Learning, Embeddings and Metric Learning

·         Transfer Learning, Domain Adaptation and Few Shot Learning

 

·         Distributed, Parallel and Cloud Native Data Mining

·         Real Time Analytics and Data Stream Mining

·         High Performance Data Mining Algorithms

·         Federated Learning, Edge Analytics and Privacy Preserving ML

·         Data Mining Systems, Infrastructure and GPU/TPU Acceleration

 

 

·         Text Mining, NLP and Large Language Models

·         Web Mining, Web Behavior Analytics and Clickstream Mining

·         Social Network Analysis, Influence Modeling and Community Detection

·         Multimedia Mining (Image, Video, Audio, Multimodal Fusion)

·         Information Retrieval, Ranking and Search Based Mining

 

·         Graph Mining, Graph Neural Networks (GNNs) and Network Embeddings

·         Spatial, Spatio Temporal and Mobility Data Mining

·         Time Series Analysis, Forecasting and Anomaly Detection

·         Mining Heterogeneous, High Dimensional and Low Quality Data

·         IoT, Sensor and Cyber Physical Data Analytics

 

 

·         Data Cleaning, Noise Reduction and Missing Data Handling

·         Feature Engineering, Feature Selection and Dimensionality Reduction

·         Data Centric AI (data selection, augmentation, labeling, weak supervision)

·         Data Integration, Warehousing, ETL and Lakehouse Architectures

·         Interactive Data Exploration, Visualization and Human in the Loop Analytics

 

 

·         Explainable AI (XAI) and Interpretable Models

·         Fairness, Bias Detection and Responsible Data Science

·         Privacy Preserving Data Mining (Differential Privacy, Secure Computation)

·         Adversarial Attacks, Robustness and Security in Data Mining

·         Data Governance, Lineage, Compliance and Auditability

 

·         Knowledge Processing, Reasoning and Inference

·         Knowledge Graphs, Ontologies and Semantic Technologies

·         Decision Support Systems and Predictive Analytics

·         Consolidation, Evaluation and Explanation of Discovered Knowledge

·         Human AI Collaboration in Data Analysis and Decision Making

 

 

·         Collaborative Filtering and Matrix Factorization

·         Sequential, Context Aware and Deep Learning Based Recommendation

·         LLM Enhanced Recommendation and Retrieval Augmented Systems

·         Fairness, Robustness and Evaluation in Recommender Systems

·         Applications in E commerce, Media, Education and Social Platforms

 

 

·         Synthetic Tabular, Time Series and Multimodal Data Generation

·         Simulation Based Data Mining

·         Privacy Preserving Synthetic Data

·         Data Augmentation for ML and Data Mining

·         Evaluation of Synthetic Data Quality

 

 

·         Bioinformatics, Computational Biology and Healthcare Analytics

·         Financial Modeling, Fraud Detection and Risk Analytics

·         Educational Data Mining and Learning Analytics

·         Marketing, E commerce and Customer Behavior Modeling

·         Smart Cities, Transportation, Climate and Environmental Analytics

 

 

Authors are invited to submit papers through the conference Submission System by May 16, 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 46) in Computer Science & Information Technology (CS & IT) series (Confirmed).

 

 

Selected papers presented at CDKP 2026, following an additional round of revisions, will be considered for publication in 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 Grid Computing & Applications (IJGCA)

·         Information Technology in Industry (ITII)

 

 

·         Submission Deadline: May 16, 2026

 

·         Authors Notification: June 13, 2026

 

·         Registration & Camera-Ready Paper Due: June 16, 2026

 

Contact Us: cdkp@cdkp2026.org