IEEE Transactions on Knowledge and Data Engineering

6.3k papers and 221.2k indexed citations i.

About

The 6.3k papers published in IEEE Transactions on Knowledge and Data Engineering in the last decades have received a total of 221.2k indexed citations. Papers published in IEEE Transactions on Knowledge and Data Engineering usually cover Artificial Intelligence (3.7k papers), Computer Networks and Communications (1.9k papers) and Information Systems (1.7k papers) specifically the topics of Data Management and Algorithms (1.4k papers), Advanced Database Systems and Queries (949 papers) and Advanced Graph Neural Networks (685 papers). The most active scholars publishing in IEEE Transactions on Knowledge and Data Engineering are Qiang Yang, Sinno Jialin Pan, Haibo He, Alexander Tuzhilin, Gediminas Adomavičius, Philip S. Yu, Zhi‐Hua Zhou, Jiawei Han, Min-Ling Zhang and Mohammed J. Zaki.

In The Last Decade

Fields of papers published in IEEE Transactions on Knowledge and Data Engineering

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

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).

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.

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2025