International Journal of Database Theory and Application

Aims & Scope

IJDTA aims to facilitate and support research related to database theory and application technology.

Our Journal provides a chance for academic and industry professionals to discuss recent progress in the area of database theory and application technology.

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Mining Educational Data to Predict Student’s academic Performance using Ensemble Methods

  Citation: 204

  Authors: Elaf Abu, Thair, Ibrahim

• KNN based Machine Learning Approach for Text and Document Mining

  Citation: 169

  Authors: Vishwanath, Vinay, Pinki, Jordan

• A Comprehensive Survey on Support Vector Machine in Data Mining Tasks: Applications & Challenges

  Citation: 112

  Authors: Janmenjoy, Bighnaraj, H. S.

• A MapReduce Implementation of C4.5 Decision Tree Algorithm

  Citation: 109

  Authors: Wei, Wei

• Analysis of KDD CUP 99 Dataset using Clustering based Data Mining

  Citation: 71

  Authors: Mohammad Khubeb, Shams

• Research of Decision Tree Classification Algorithm in Data Mining

  Citation: 57

  Authors: Qing-yun, Chun-ping, Hao

• Implementation of the Fuzzy C-Means Clustering Algorithm in Meteorological Data

  Citation: 39

  Authors: Yinghua, Tinghuai, Changhong, Xiaoyu, Wei, Shui Ming

• A Study on Software Metrics based Software Defect Prediction using Data Mining and Machine Learning Techniques

  Citation: 37

  Authors: Manjula.C.M., Lilly Florence, Arti

• Stream Data Mining: Platforms, Algorithms, Performance Evaluators and Research Trends

  Citation: 35

  Authors: Bakshi Rohit, Sonali

• Optimal Predictive analytics of Pima Diabetics using Deep Learning

  Citation: 32

  Authors: H., N.Ch.S.N, Ronnie D.