Fleur Mougin
- Molecular Biology
- Artificial Intelligence top 5%
- Toxicology top 2%
- Computational Theory and Mathematics top 10%
- Health Information Management top 5%
- Co-authors
- Gayo DialloOlivier BodenreiderAnita BurgunFrantz ThiessardNatalia GrabarVianney JouhetAnnie Fourrier‐RéglatJean-Charles Dufour
- Topics
- Biomedical Text Mining and Ontologies (36 papers)Semantic Web and Ontologies (26 papers)Natural Language Processing Techniques (14 papers)
- Partner nations
- FranceUnited StatesItaly
In The Last Decade
Fleur Mougin
50 papers receiving 458 citations
Peers
Comparison fields: 5 of 87
- Molecular Biology 270
- Artificial Intelligence 240
- Toxicology 84
- Computational Theory and Mathematics 65
- Health Information Management 46
Countries citing papers authored by Fleur Mougin
This map shows the geographic impact of Fleur Mougin'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 Fleur Mougin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fleur Mougin more than expected).
Fields of papers citing papers by Fleur Mougin
This network shows the impact of papers produced by Fleur Mougin. 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 Fleur Mougin. The network helps show where Fleur Mougin may publish in the future.
Co-authorship network of co-authors of Fleur Mougin
This figure shows the co-authorship network connecting the top 25 collaborators of Fleur Mougin. A scholar is included among the top collaborators of Fleur Mougin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fleur Mougin. Fleur Mougin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Pre-Trained Embeddings for Enhancing Multi-Hop Reasoning | 1 |
| 3 | KOSonto: An ontology for knowledge organization systems, their constituents, and their referents | 2 |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 18 | |
| 8 | 9 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 10 | |
| 12 | 10 | |
| 13 | 16 | |
| 14 | A k-nearest neighbor based method for improving large scale biomedical document indexing | 2 |
| 15 | Description of the POMELO System for the Task 2 of QALD-2014. | 4 |
| 16 | Query Expansion using External Resources for Improving Information Retrieval in the Biomedical Domain. | 7 |
| 17 | 63 | |
| 18 | 17 | |
| 19 | Evidence in pharmacovigilance: extracting adverse drug reactions articles from MEDLINE to link them to case databases. | 3 |
| 20 | 13 |
About Fleur Mougin
Fleur Mougin is a scholar working on Health Information Management, Toxicology and Artificial Intelligence, having authored 52 papers that have together received 484 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (36 papers), Semantic Web and Ontologies (26 papers) and Natural Language Processing Techniques (14 papers). The work is most often cited by research in Toxicology (84 citations), Health Information Management (46 citations) and Artificial Intelligence (240 citations). Fleur Mougin has collaborated with scholars based in France, United States and Italy. Frequent co-authors include Gayo Diallo, Olivier Bodenreider, Anita Burgun, Frantz Thiessard, Natalia Grabar, Vianney Jouhet, Annie Fourrier‐Réglat, Jean-Charles Dufour, Paul Avillach and Alexandre Pariente. Their work appears in journals such as PLoS ONE, BMC Bioinformatics and Journal of the American Medical Informatics Association.
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.