Michel Buffa

62 papers receiving 565 citations

Peers

Michel Buffa
Comparison fields: 5 of 59
  • Artificial Intelligence 316
  • Computer Vision and Pattern Recognition 113
  • Statistical and Nonlinear Physics 51
  • Information Systems 110
  • Communication 37
Replace Xin Yu Jin with:
Xin Yu Jin China
Xidao Wen United States
K. K. Bharadwaj India
Elöd Egyed‐Zsigmond France
Sofia Ceppi Italy
Dustin Arendt United States
Cindy Xide Lin United States
Antoine Boutet France
Mohamed Bouguessa Canada
Michel Crampes France
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Citations per year

Countries citing papers authored by Michel Buffa

Since Specialization
Citations

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

Fields of papers citing papers by Michel Buffa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michel Buffa, 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 Michel Buffa Line = papers co-authored together Michel Buffa links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007122
2 200962
3 200657
4
A State of the Art on Social Network Analysis and its Applications on a Semantic Web
200838
5 201127
6 200226
7 201125
8 200219
9
Using a Semantic Wiki in Communities of Practice
200816
10 200816
11 201112
12
WASABI: a Two Million Song Database Project with Audio and Cultural Metadata plus WebAudio enhanced Client Applications
201712
13 200611
14 201211
15
SweetWiki : Semantic WEb Enabled Technologies in Wiki
200610
16 20029
17
Helping online communities to semantically enrich folksonomies
20109
18 20189
19 20177
20 20217

About Michel Buffa

Michel Buffa is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Statistical and Nonlinear Physics and Information Systems, having authored 70 papers that have together received 609 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (31 papers), Music Technology and Sound Studies (27 papers), Music and Audio Processing (5 papers), Robotics and Sensor-Based Localization (4 papers), Complex Network Analysis Techniques (4 papers), Robotic Path Planning Algorithms (2 papers), Access Control and Trust (2 papers) and Data Visualization and Analytics (2 papers). The work is most often cited by research in Artificial Intelligence (316 citations), Computer Vision and Pattern Recognition (113 citations), Statistical and Nonlinear Physics (51 citations), Information Systems (110 citations) and Communication (37 citations). Michel Buffa has collaborated with scholars based in France, Italy and United Kingdom. Frequent co-authors include Fabien L. Gandon, Guillaume Erétéo, Peter T. Sander, Catherine Faron Zucker, Olivier Corby, Jérôme Lebrun, Martial Hebert, Olivier D. Faugeras, Alain Giboin and Zhengyou Zhang. Their work appears in journals such as Journal of the Audio Engineering Society, Journal of Web Semantics, Language Resources and Evaluation, Machine Vision and Applications and Lecture notes in computer science.

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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