Benoît Habert

63 papers receiving 544 citations

Peers

Benoît Habert
Comparison fields: 5 of 63
  • Language and Linguistics 235
  • Linguistics and Language 92
  • Philosophy 173
  • Radiation 115
  • Artificial Intelligence 343
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Pierre Guiraud Chile
Hans Smessaert Belgium
Jean-Yves Béziau Brazil
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Hans Hermes Germany
Lorenz Demey Belgium
R. L. Goodstein United Kingdom
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Countries citing papers authored by Benoît Habert

Since Specialization
Citations

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

Fields of papers citing papers by Benoît Habert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Benoît Habert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Benoît Habert Line = papers co-authored together Benoît Habert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Les linguistiques de corpus
1997118
2 199695
3 201031
4 199827
5 200927
6 199626
7
Benoît Habert, Adeline Nazarenko, André Salem, Les linguistiques de corpus. Armand Colin, Paris, 1997
199826
8
Building a text corpus for representing the variety of medical language.
200125
9 200722
10
Corpus-based identification and refinement of semantic classes.
199721
11 198920
12
Instruments et ressources électroniques pour le français
200517
13 200814
14
A disfluency study for cleaning spontaneous speech automatic transcripts and improving speech language models
200314
15 200114
16
A quantitative study of disfluencies in French broadcast interviews
200513
17 201213
18 201812
19 200210
20 19879

About Benoît Habert

Benoît Habert is a scholar working on Philosophy, Language and Linguistics, Linguistics and Language, Artificial Intelligence and Radiation, having authored 71 papers that have together received 690 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (24 papers), Linguistics and Discourse Analysis (20 papers), French Language Learning Methods (12 papers), Nuclear reactor physics and engineering (9 papers), Nuclear Physics and Applications (8 papers), linguistics and terminology studies (7 papers), Biomedical Text Mining and Ontologies (6 papers) and Lexicography and Language Studies (5 papers). The work is most often cited by research in Language and Linguistics (235 citations), Linguistics and Language (92 citations), Philosophy (173 citations), Radiation (115 citations) and Artificial Intelligence (343 citations). Benoît Habert has collaborated with scholars based in France, Belgium and United States. Frequent co-authors include Adeline Nazarenko, André Salem, Gilles Noguère, Cyrille De Saint Jean, Béatrice Daille, Christian Jacquemin, Pierre Zweigenbaum, Gilles Adda, Philippe Boula de Mareüil and Jacques Bouaud. Their work appears in journals such as Language Resources and Evaluation, Nuclear Science and Engineering, Terminology International Journal of Theoretical and Applied Issues in Specialized Communication, Nuclear Data Sheets and Journal of the Korean Physical Society.

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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