DOI: 10.20894/IJDMTA.

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Volume 1 Issue 1
Volume 1 Issue 2
Volume 2 Issue 1
Volume 2 Issue 2
Volume 3 Issue 1
Volume 3 Issue 2
Volume 4 Issue 1
Volume 4 Issue 2
Volume 5 Issue 1
Volume 5 Issue 2

IJDMTAis 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.

Scope of the Journal

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