IEEE Transactions on Knowledge and Data Engineering Impact Factor, Quartile, Indexing, Ranking
IEEE Transactions on Knowledge and Data Engineering (ITKDE) is a scholarly journal dedicated to publishing research in the field of Computer Science, and Published by Institute of Electrical and Electronics Engineers.
The Print-ISSN of IEEE Transactions on Knowledge and Data Engineering is 1041-4347 and its abbreviation is IEEE Trans Knowl Data Eng.
The latest Impact Factor of the IEEE Transactions on Knowledge and Data Engineering for 2024-2025 is 8.9.
The scope of the IEEE Transactions on Knowledge and Data Engineering includes the knowledge and data engineering aspects of computer science, artificial intelligence, electrical engineering, computer engineering, and other appropriate fields. This Transactions provides an international and interdisciplinary forum to communicate results of new developments in knowledge and data engineering and the feasibility studies of these ideas in hardware and software. Specific areas to be covered are as follows: Fields and Areas of Knowledge and Data Engineering: (a) Knowledge and data engineering aspects of knowledge-based and expert systems, (b) Artificial Intelligence techniques relating to knowledge and data management, (c) Knowledge and data engineering tools and techniques, (d) Distributed knowledge base and database processing, (e) Real-time knowledge bases and databases, (f) Architectures for knowledge and data based systems, (g) Data management methodologies, (h) Database design and modeling, (i) Query, design, and implementation languages, (j) Integrity, security, and fault tolerance, (k) Distributed database control, (l) Statistical databases, (m) System integration and modeling of these systems, (n) Algorithms for these systems, (o) Performance evaluation of these algorithms, (p) Data communications aspects of these systems, (q) Applications of these systems.
In the context of academic journals, "Metrics and Rankings" refer to various measures and evaluations used to assess the quality, influence, and impact of a journal.
Below are the metrics and rankings for the journal IEEE Transactions on Knowledge and Data Engineering
Abstracting and Indexing (A&I) refers to the processes that help organize and categorize academic journals, making them easier to find and access for researchers and scholars
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