Christina Unger

18 papers and 330 indexed citations i.

About

Christina Unger is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Christina Unger has authored 18 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 4 papers in Molecular Biology and 2 papers in Information Systems. Recurrent topics in Christina Unger’s work include Natural Language Processing Techniques (16 papers), Semantic Web and Ontologies (15 papers) and Topic Modeling (10 papers). Christina Unger is often cited by papers focused on Natural Language Processing Techniques (16 papers), Semantic Web and Ontologies (15 papers) and Topic Modeling (10 papers). Christina Unger collaborates with scholars based in Germany, United Kingdom and France. Christina Unger's co-authors include Philipp Cimiano, Axel-Cyrille Ngonga Ngomo, Lorenz Bühmann, Jens Lehmann, Dániel Gerber, Vanessa López, Enrico Motta, Sebastian Walter, John P. McCrae and Ricardo Usbeck and has published in prestigious journals such as Brain Research, Language Resources and Evaluation and Data & Knowledge Engineering.

In The Last Decade

Co-authorship network of co-authors of Christina Unger i

Fields of papers citing papers by Christina Unger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christina Unger. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Christina Unger. The network helps show where Christina Unger may publish in the future.

Countries citing papers authored by Christina Unger

Since Specialization
Citations

This map shows the geographic impact of Christina Unger's research. 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 Christina Unger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christina Unger 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