International Journal of Data Mining Techniques and Applications (IJDMTA) is a peer-reviewed bi-annual journal that publishes high-quality papers on all aspects of IJDMTA. The primary objective of IJDMTA is to be an authoritative International forum for delivering both theoretical and innovative applied researches in the data mining concepts, to implementations. The IJDMTA publishes original research contributions, surveys, and experimental studies with technical advances.
The IJDMTA is publishes research and technical papers, both short and long. We welcome authors to submit the research and technical papers in the following area
Agent-based Data Analysis and Knowledge Discovery | Industrial Applications of Business Analytics and Optimization |
Big Data Analysis | Intelligent Multi-gent Systems |
Convergence of Data Mining and Intelligent IT Applications | Intrusion Detection and Access Control Techniques |
CRM, e-Marketing and e-Commerce | IT Applications for Agriculture Management |
Data Mining Algorithms | IT Software Development and Methodology |
Data Mining for Biological and Environmental Problems | Knowledge Management |
Data Mining Techniques for IT Applications | Mining Sequence Data and Time Series Data |
Data Modeling and Engineering | Novel Applications of Intelligent IT Techniques for Complex Systems |
Data Pre-Processing, Data Transformation and Dimensionality Reduction | Prediction Systems |
Decision Analysis and Decision Support Systems | Real-time Mining, Data Stream Mining, and Dynamic Data Mining |
Distributed Data Mining and Mining Multi-agent Data | Security and Forensic Applications |
Feature Extraction and Feature Selection | Security, Privacy and Data Integrity |
Graph Mining and Semi-Structured Data | Spatial and Temporal Data Mining |
Healthcare Applications and Medical Diagnosis | Statistical Learning Theory and Neural Network Research |
High Dimensional Data and High Speed Data Streams | Uncertainty Modeling in Data Mining |
Unifying Theory of Data Mining | Visual Mining and Data Visualization |
Web Mining |