Pascale Sébillot

23 papers receiving 102 citations

Peers

Pascale Sébillot
Comparison fields: 5 of 28
  • Artificial Intelligence 104
  • Computer Vision and Pattern Recognition 34
  • Signal Processing 14
  • Information Systems 13
  • Media Technology 5
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Citations per field
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Citations per year

Countries citing papers authored by Pascale Sébillot

Since Specialization
Citations

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

Fields of papers citing papers by Pascale Sébillot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pascale Sébillot

This figure shows the co-authorship network connecting the top 25 collaborators of Pascale Sébillot. A scholar is included among the top collaborators of Pascale Sébillot 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 Pascale Sébillot. Pascale Sébillot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 5
3 2
4 13
5 12
6 0
7 16
8 12
9
On the Use of Web Resources and Natural Language Processing Techniques to Improve Automatic Speech Recognition Systems.
1
10 1
11 4
12 1
13
Contributions des techniques du traitement automatique des langues à la recherche d'information
5
14
Extension de requêtes par lien sémantique nom-verbe acquis sur corpus
3
15 2
16
Learning semantic lexicons from a part-of-speech and semantically tagged corpus using inductive logic programming
9
17 11
18
Automatic generation of sets of keywords for theme characterization and detection
2
19 4
20
Calculability of the Semantics of English Nominal Compounds: Combining General Linguistic Rules and Corpus-based Semantic Information
0

About Pascale Sébillot

Pascale Sébillot is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 28 papers that have together received 122 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (24 papers), Topic Modeling (15 papers) and Semantic Web and Ontologies (5 papers). The work is most often cited by research in Artificial Intelligence (104 citations), Computer Vision and Pattern Recognition (34 citations) and Signal Processing (14 citations). Pascale Sébillot has collaborated with scholars based in France, Czechia and Switzerland. Frequent co-authors include Guillaume Gravier, Vincent Claveau, Stéphane Huet, Pierrette Bouillon, Mathias Rossignol, Christophe García, Franck Mamalet, Guillaume Gravier, François Goasdoué and Emmanuel Morin. Their work appears in journals such as American Journal of Ophthalmology, Journal of Machine Learning Research and Computer Assisted Language Learning.

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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