JUCS - Journal of Universal Computer Science

1.7k papers and 10.6k indexed citations i.

About

The 1.7k papers published in JUCS - Journal of Universal Computer Science in the last decades have received a total of 10.6k indexed citations. Papers published in JUCS - Journal of Universal Computer Science usually cover Artificial Intelligence (631 papers), Information Systems (523 papers) and Computer Networks and Communications (342 papers) specifically the topics of Semantic Web and Ontologies (171 papers), QoS-Aware Web Services Composition and Semantic Matching (170 papers) and Advanced Software Engineering Methodologies (94 papers). The most active scholars publishing in JUCS - Journal of Universal Computer Science are Hermann Maurer, Jason J. Jung, Daniel D. Suthers, Lutz Prechelt, Kwok‐wing Chau, Jun Zhang, Michæl Philippsen, Guido Malpohl, Gheorghe Pǎun and Kalevi Kilkki.

In The Last Decade

Fields of papers published in JUCS - Journal of Universal Computer Science

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in JUCS - Journal of Universal Computer Science. 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 JUCS - Journal of Universal Computer Science.

Countries where authors publish in JUCS - Journal of Universal Computer Science

Since Specialization
Citations

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