Mathieu d’Aquin

4.3k citations
195 papers · 3.4k · h-index 32

Impact in

Papers in

Mathieu d’Aquin

190 papers receiving 3.1k citations

Peers

Mathieu d’Aquin
Comparison fields: 5 of 97
  • Artificial Intelligence 2.5k
  • Computer Science Applications 171
  • Information Systems 409
  • Media Technology 74
  • Health Informatics 19
Replace Praveen K. Paritosh with:
Praveen K. Paritosh United States
Francesco Orciuoli Italy
Markus Krötzsch Germany
Hai Zhuge China
Francesco Colace Italy
Richard Cyganiak A Ireland
Georgi Kobilarov Germany
Hyacinth S. Nwana United Kingdom
Carlos Iván Chesñevar Argentina
Stefanos Gritzalis Greece
Mathieu d’Aquin relative to Praveen K. Paritosh United States Praveen K. Paritosh's profile →
Citations per field
00.5×2×3.0×
Praveen K. Paritosh · 1×
Citations per year

Countries citing papers authored by Mathieu d’Aquin

Since Specialization
Citations

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

Fields of papers citing papers by Mathieu d’Aquin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mathieu d’Aquin. 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 Mathieu d’Aquin. The network helps show where Mathieu d’Aquin may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 195 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006161
2 2008131
3 2011128
4 2013119
5 2008102
6 201180
7 200878
8 201276
9
Using the semantic web as background knowledge for ontology mapping
200666
10
Characterizing knowledge on the semantic web with Watson
200765
11 201463
12 201161
13 200960
14 200759
15 201858
16
Modularization: a key for the dynamic selection of relevant knowledge components
200656
17
The NeOn Ontology Engineering Toolkit
200855
18
WATSON: a gateway for the semantic web
200751
19 200649
20 201349

About Mathieu d’Aquin

Mathieu d’Aquin is a scholar working on Artificial Intelligence, Computer Science Applications, Information Systems, Health Information Management and Management Science and Operations Research, having authored 195 papers that have together received 3.4k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (141 papers), Online Learning and Analytics (12 papers), AI-based Problem Solving and Planning (10 papers), Open Education and E-Learning (9 papers), Research Data Management Practices (8 papers), Data Mining Algorithms and Applications (7 papers), Digital Humanities and Scholarship (5 papers) and Access Control and Trust (4 papers). The work is most often cited by research in Artificial Intelligence (2.5k citations), Computer Science Applications (171 citations), Information Systems (409 citations), Media Technology (74 citations) and Health Informatics (19 citations). Mathieu d’Aquin has collaborated with scholars based in United Kingdom, France and Germany. Frequent co-authors include Enrico Motta, Marta Sabou, Jean Lieber, Amedeo Napoli, Natalya Fridman Noy, Andriy Nikolov, Sofia Angeletou, Laurian Gridinoc, Fouad Zablith and Ilaria Tiddi. Their work appears in journals such as Semantic Web, Lecture notes in computer science, IEEE Intelligent Systems, The Knowledge Engineering Review and IEEE Access.

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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