Journal of Data Science and Intelligent Systems

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The Journal of Data Science and Intelligent Systems (JDSIS) is an international, peer-reviewed, interdisciplinary journal that provides in-depth coverage of the latest advances in the closely related fields of data science and intelligent systems.

JDSIS considers researches that focus on data integration, data information and knowledge extraction, and data application in a wide range of fields, including health, education, agriculture, biology, medicine, finance, environment, engineering, commerce, and industry. By integrating of data with computer science, artificial intelligence, and other appropriate methods, the scope of JDSIS covers the entire process of areas of Data Science and Intelligent Systems.

JDSIS considers researches that focus on data integration, data information and knowledge extraction, and data application in a wide range of fields, including health, education, agriculture, biology, medicine, finance, environment, engineering, commerce, and industry. By integration of data with computer science, artificial intelligence, and other appropriate methods, the scope of JDSIS covers the entire process of areas of Data Science and Intelligent Systems:

  • Big data itself, i.e., the nature and quality of the data

  • Data science and intelligent systems aspects of knowledge-based and expert systems

  • Principles and theories of data acquisition, extraction, and integration

  • Techniques and systems used to analyze and manage big data

  • Methods and algorithms designed for data mining, online analysis, decision-making, and other data-intensive computing

  • Artificial Intelligence techniques relating to data science and intelligent systems

  • Artificial Intelligence for database (AI4DB) and database for Artificial Intelligence (DB4AI) techniques

  • Knowledge and data engineering tools and techniques

  • Data management methodologies

  • Distributed and parallel databases processing

  • Architectures for knowledge and data-based intelligent systems

  • Database design and modeling

  • System integration and modeling of intelligent systems

  • Algorithms and technologies for intelligent systems

  • Hardware systems and software systems for data computing

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