André Mayers

408 total citations
25 papers, 206 citations indexed

About

André Mayers is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Science Applications. According to data from OpenAlex, André Mayers has authored 25 papers receiving a total of 206 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Computer Science Applications. Recurrent topics in André Mayers's work include Intelligent Tutoring Systems and Adaptive Learning (14 papers), AI-based Problem Solving and Planning (8 papers) and Semantic Web and Ontologies (5 papers). André Mayers is often cited by papers focused on Intelligent Tutoring Systems and Adaptive Learning (14 papers), AI-based Problem Solving and Planning (8 papers) and Semantic Web and Ontologies (5 papers). André Mayers collaborates with scholars based in Canada, United States and United Arab Emirates. André Mayers's co-authors include Shengrui Wang, Philippe Fournier‐Viger, Roger Nkambou, Usef Faghihi, Engelbert Mephu Nguifo, Claude Frasson, Luc Paquette, François Courtemanche, Pierre Poirier and Luigi Buglione and has published in prestigious journals such as Expert Systems with Applications, IEEE Systems Journal and Data Mining and Knowledge Discovery.

In The Last Decade

André Mayers

23 papers receiving 194 citations

Peers

André Mayers
Comparison fields: 5 of 54
  • Artificial Intelligence 137
  • Computer Vision and Pattern Recognition 49
  • Computer Science Applications 38
  • Information Systems 34
  • Developmental and Educational Psychology 22
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Todor Mihaylov Germany
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Citations per field, relative to André Mayers
André Mayers · 1×
Citations per year, relative to André Mayers
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Countries citing papers authored by André Mayers

Since Specialization
Citations

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

Fields of papers citing papers by André Mayers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of André Mayers

This figure shows the co-authorship network connecting the top 25 collaborators of André Mayers. A scholar is included among the top collaborators of André Mayers 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 André Mayers. André Mayers 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
# Work Indexed citations
1 6
2 3
3 17
4 31
5 62
6 4
7
A Framework for Evaluating Semantic Knowledge in Problem-Solving- Based Intelligent Tutoring Systems
1
8 3
9 8
10 1
11 13
12 7
13
Tools and Structures for Modelling Domain/User Knowledge in Virtual Learning
1
14 2
15 2
16 2
17 3
18
Dynamic User Modelling through Virtual Course : Toward a Cognitive Approach to Represent Knowledge for E-Learning
0
19
Knowledge modeling for the design of a KBS in the functional size measurement domain
4
20 9

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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