Max Chevalier

808 citations
23 papers · 114 · h-index 6

Impact in

Papers in

    • Recommender Systems and Techniques 7
    • Information Retrieval and Search Behavior 3
    • Expert finding and Q&A systems 2
    • Semantic Web and Ontologies 5
    • Advanced Text Analysis Techniques 3

Max Chevalier

21 papers receiving 107 citations

Peers

Max Chevalier
Comparison fields: 5 of 45
  • Information Systems 39
  • Computer Science Applications 9
  • Signal Processing 16
  • Artificial Intelligence 41
  • Computer Networks and Communications 22
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Citations per field
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Citations per year

Countries citing papers authored by Max Chevalier

Since Specialization
Citations

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

Fields of papers citing papers by Max Chevalier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Max Chevalier, 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 Max Chevalier Line = papers co-authored together Max Chevalier links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202232
2 201513
3 200711
4
A Social Validation of Collaborative Annotations on Digital Documents
200510
5 20088
6 20148
7 20204
8
ISIDOR: A Visualisation Interface for Advanced Information Retrieval.
20003
9 20223
10
Diversity in Recommender Systems: Bridging the gap between users and systems
20113
11 20103
12
Validation sociale d'annotations collectives : argumentation bipolaire graduelle pour la théorie sociale de l'information.
20062
13
Interface coopérative et adaptative pour la Recherche d'Information sur le Web.
20032
14 20202
15 20092
16 20152
17 20222
18
Profiles semantics and matching flexibility for resources access.
20051
19 20101
20
Interopérabilité de Profils pour l'Accès à des Ressources.
20061

About Max Chevalier

Max Chevalier is a scholar working on Information Systems, Artificial Intelligence, Statistical and Nonlinear Physics, Information Systems and Management and Signal Processing, having authored 23 papers that have together received 114 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (7 papers), Semantic Web and Ontologies (5 papers), Data Management and Algorithms (3 papers), Personal Information Management and User Behavior (3 papers), Advanced Text Analysis Techniques (3 papers), Information Retrieval and Search Behavior (3 papers), Mobile Crowdsensing and Crowdsourcing (2 papers) and Expert finding and Q&A systems (2 papers). The work is most often cited by research in Information Systems (39 citations), Computer Science Applications (9 citations), Signal Processing (16 citations), Artificial Intelligence (41 citations) and Computer Networks and Communications (22 citations). Max Chevalier has collaborated with scholars based in France, Italy and Germany. Frequent co-authors include Christine Julien, Olivier Teste, Claude Chrisment, Guillaume Cabanac, Corentin Lapeyre, Arlind Kopliku, Ronan Tournier, Valentin Grouès, Massimo Melucci and André Tricot. Their work appears in journals such as Computational Geosciences, Aerospace Science and Technology, International Journal on Digital Libraries, ACM SIGIR Forum and Brazilian Journal of Operations & Production Management.

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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