Mathieu Roche

2.3k citations
206 papers · 1.4k · h-index 19

Impact in

    • Advanced Text Analysis Techniques
    • Topic Modeling
    • Natural Language Processing Techniques
    • Semantic Web and Ontologies
    • Sentiment Analysis and Opinion Mining
    • Web Data Mining and Analysis

Papers in

    • Natural Language Processing Techniques 67
    • Advanced Text Analysis Techniques 63
    • Topic Modeling 44
    • Semantic Web and Ontologies 42
    • Sentiment Analysis and Opinion Mining 16
    • Biomedical Text Mining and Ontologies 34

Mathieu Roche

182 papers receiving 1.3k citations

Peers

Mathieu Roche
Comparison fields: 5 of 125
  • Artificial Intelligence 782
  • Information Systems 350
  • Linguistics and Language 71
  • Geography, Planning and Development 55
  • Signal Processing 90
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Citations per field
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Citations per year

Countries citing papers authored by Mathieu Roche

Since Specialization
Citations

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

Fields of papers citing papers by Mathieu Roche

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 206 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200869
2 201551
3 201847
4 201945
5 201844
6 202142
7 201734
8 201629
9 201128
10 201128
11
Web Analyzing Traffic Challenge: Description and Results
200726
12 201326
13 200925
14 201421
15 202020
16 201420
17 202019
18 201219
19 201418
20 202118

About Mathieu Roche

Mathieu Roche is a scholar working on Artificial Intelligence, Molecular Biology, Information Systems, Epidemiology and Language and Linguistics, having authored 206 papers that have together received 1.4k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (67 papers), Advanced Text Analysis Techniques (63 papers), Topic Modeling (44 papers), Semantic Web and Ontologies (42 papers), Biomedical Text Mining and Ontologies (34 papers), Data-Driven Disease Surveillance (31 papers), Web Data Mining and Analysis (16 papers) and Sentiment Analysis and Opinion Mining (16 papers). The work is most often cited by research in Artificial Intelligence (782 citations), Information Systems (350 citations), Linguistics and Language (71 citations), Geography, Planning and Development (55 citations) and Signal Processing (90 citations). Mathieu Roche has collaborated with scholars based in France, Canada and Sweden. Frequent co-authors include Maguelonne Teisseire, Pascal Poncelet, Violaine Prince, Elena Arsevska, Juan Antonio Lossio-Ventura, Clément Jonquet, Renaud Lancelot, Gérard Dray, Brett Drury and Yves Kodratoff. Their work appears in journals such as Data in Brief, Expert Systems with Applications, Computers and Electronics in Agriculture, Lecture notes in computer science and Language Resources and Evaluation.

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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