IEEE Transactions on Knowledge and Data Engineering
6.1k papers
receiving
270.1k citations
Peers
IEEE Transactions on Knowledge and Data Engineering
Comparison fields: 5 of 242
Artificial Intelligence155.2k
Information Systems78.9k
Computer Vision and Pattern Recognition57.9k
Computer Networks and Communications56.4k
Signal Processing47.0k
Replace Machine Learning with:
Machine LearningUnited States
NeurocomputingChina
Knowledge-Based SystemsChina
Communications of the ACMUnited States
Information SciencesChina
ACM Computing SurveysUnited States
Proceedings of the IEEEUnited States
Expert Systems with ApplicationsChina
Journal of Machine Learning ResearchUnited States
IEEE AccessChina
IEEE Transactions on Knowledge and Data Engineeringrelative toMachine LearningUnited StatesMachine Learning's profile →
Citations per field
00.5×1.5×2.2×
Machine Learning · 1×
×0.8155k/192kAI
×1.879k/44kIS
×0.958k/61kCVPR
×2.256k/26kCNC
×1.747k/28kSP
Citations per year
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Countries where authors publish in IEEE Transactions on Knowledge and Data Engineering
Since Specialization
Citations
This map shows the geographic impact of research published in IEEE Transactions on Knowledge and Data Engineering. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in IEEE Transactions on Knowledge and Data Engineering with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites IEEE Transactions on Knowledge and Data Engineering more than expected).
Fields of papers published in IEEE Transactions on Knowledge and Data Engineering
This network shows the impact of papers published in IEEE Transactions on Knowledge and Data Engineering. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in IEEE Transactions on Knowledge and Data Engineering.
About IEEE Transactions on Knowledge and Data Engineering
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.