International Journal of Data Mining Science (IJDAT)

The International Journal of Data Mining Science (IJDAT) seeks to promote and disseminate knowledge of the various topics and scientific knowledge of data mining. The journal aims to present to the international community important results of work in the fields of data mining research, development, application, design or algorithms. The journal also aims to help researchers, scientists, manufacturers, institutions, world agencies, societies, etc. to keep up with new developments in theory and applications and to provide alternative solutions.

The International Journal of Data Mining Science is a quarterly published, open source journal and operates an online submission with the peer review system allowing authors to submit articles online and track their progress via its web interface. The journal aims for a publication speed of 60 days from submission until final publication.

The coverage of IJDAT includes the following areas, but not limited to:

  • Data Mining, Data Science and Big Data,
  • Data Warehouse, Clustering, Visualization
  • Security, Privacy,
  • Big DaaS
  • Scalable Computing, Cloud Computing,
  • Knowledge Discovery, Integration, Transformation
  • Information Retrieval,
  • Data Classification, Regression, Cleaning,
  • Smart Cities & Energy
  • Social Media, Social Networking, Social Data,
  • Semantics,
  • IoT
  • Multimedia
  • Mobile Computing
  • Sensors, Networks, Devices
  • Biometric,
  • Sustainability
  • Bioinformatics,
  • Artificial Intelligence,
  • Data Science
  • Recent Theory, Trends, Technologies and Applications,
  • Future Directions and Challenges in Data Mining ,
  • Industrial Challenges in Data Mining ,
  • Demo Applications,