Natalia Grabar

83 papers and 491 indexed citations i.

About

Natalia Grabar is a scholar working on Artificial Intelligence, Molecular Biology and Language and Linguistics. According to data from OpenAlex, Natalia Grabar has authored 83 papers receiving a total of 491 indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Artificial Intelligence, 46 papers in Molecular Biology and 18 papers in Language and Linguistics. Recurrent topics in Natalia Grabar’s work include Biomedical Text Mining and Ontologies (46 papers), Natural Language Processing Techniques (42 papers) and Topic Modeling (28 papers). Natalia Grabar is often cited by papers focused on Biomedical Text Mining and Ontologies (46 papers), Natural Language Processing Techniques (42 papers) and Topic Modeling (28 papers). Natalia Grabar collaborates with scholars based in France, Japan and Canada. Natalia Grabar's co-authors include Thierry Hamon, Pierre Zweigenbaum, Patrice Degoulet, Éric Zapletal, Célia Boyer, Fleur Mougin, Arnaud Gaudinat, Stéfan Darmoni, Cyril Grouin and Laura Maxim and has published in prestigious journals such as ACM Computing Surveys, Journal of the American Medical Informatics Association and Frontiers in Pharmacology.

In The Last Decade

Co-authorship network of co-authors of Natalia Grabar i

Fields of papers citing papers by Natalia Grabar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Natalia Grabar. 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 Natalia Grabar. The network helps show where Natalia Grabar may publish in the future.

Countries citing papers authored by Natalia Grabar

Since Specialization
Citations

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