Antoine Doucet

3.4k citations
76 papers · 848 indexed · h-index 15
Topics
Topic Modeling (27 papers)Natural Language Processing Techniques (21 papers)Advanced Text Analysis Techniques (14 papers)

In The Last Decade

Antoine Doucet

66 papers receiving 779 citations

Peers

Antoine Doucet
Comparison fields: 5 of 118
  • Artificial Intelligence 468
  • Computer Vision and Pattern Recognition 202
  • Information Systems 130
  • Oncology 89
  • Computer Science Applications 65
Replace Mathias Lux with:
Mathias Lux Austria
Manolis Μaragoudakis Greece
Matthias Hagen Germany
Muhammad Wasif Nisar Pakistan
Jieyu Zhao China
Claire Grover United Kingdom
El Habib Benlahmar Morocco
Mennatallah El‐Assady Germany
Antoine Doucet relative to Mathias Lux Austria Mathias Lux's profile →
Citations per field
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Mathias Lux · 1×
Citations per year

Countries citing papers authored by Antoine Doucet

Since Specialization
Citations

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

Fields of papers citing papers by Antoine Doucet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Antoine Doucet

This figure shows the co-authorship network connecting the top 25 collaborators of Antoine Doucet. A scholar is included among the top collaborators of Antoine Doucet 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 Antoine Doucet. Antoine Doucet 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 0
2 2
3 2
4 2
5 0
6 0
7 2
8 1
9 37
10 11
11 7
12 7
13 14
14 11
15 60
16 12
17 16
18 20
19
"Let Everything Turn Well in Your Wife": Generation of Adult Humor Using Lexical Constraints
31
20
Overview of INEX 2013
4

About Antoine Doucet

Antoine Doucet is a scholar working on Artificial Intelligence, Information Systems and Health Informatics, having authored 76 papers that have together received 848 indexed citations. Recurring topics across this work include Topic Modeling (27 papers), Natural Language Processing Techniques (21 papers) and Advanced Text Analysis Techniques (14 papers). The work is most often cited by research in Health Informatics (29 citations), Artificial Intelligence (468 citations) and Computer Science Applications (65 citations). Antoine Doucet has collaborated with scholars based in France, United Kingdom and Finland. Frequent co-authors include Mickaël Coustaty, Adam Jatowt, Van-Dung Hoang, Gabriella Kazai, Hannu Toivonen, Elvys Linhares Pontes, Emanuela Boroş, Alessandro Valitutti, José G. Moreno and Christophe Rigaud. Their work appears in journals such as Scientific Reports, IEEE Access and ACM Computing Surveys.

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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