KI - Künstliche Intelligenz

585 papers and 4.6k indexed citations i.

About

The 585 papers published in KI - Künstliche Intelligenz in the last decades have received a total of 4.6k indexed citations. Papers published in KI - Künstliche Intelligenz usually cover Artificial Intelligence (318 papers), Computer Vision and Pattern Recognition (101 papers) and Control and Systems Engineering (48 papers) specifically the topics of Semantic Web and Ontologies (90 papers), Logic, Reasoning, and Knowledge (80 papers) and AI-based Problem Solving and Planning (56 papers). The most active scholars publishing in KI - Künstliche Intelligenz are Radu Bogdan Rusu, Benjamin Schrauwen, Mantas Lukoševičius, Herbert Jaeger, Andreas Holzinger, Heimo Müller, André Carrington, Matthias Thimm, Jörg Lücke and Frank Hutter.

In The Last Decade

Fields of papers published in KI - Künstliche Intelligenz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in KI - Künstliche Intelligenz. 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 KI - Künstliche Intelligenz.

Countries where authors publish in KI - Künstliche Intelligenz

Since Specialization
Citations

This map shows the geographic impact of research published in KI - Künstliche Intelligenz. 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 KI - Künstliche Intelligenz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites KI - Künstliche Intelligenz 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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