Maud Ehrmann

952 citations
38 papers · 460 · h-index 12

Impact in

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

Papers in

Maud Ehrmann

33 papers receiving 401 citations

Peers

Maud Ehrmann
Comparison fields: 5 of 57
  • Artificial Intelligence 364
  • Conservation 17
  • Space and Planetary Science 5
  • Information Systems 76
  • Management Science and Operations Research 40
Replace Petri Leskinen with:
Petri Leskinen Finland
Ulli Waltinger Germany
Francesca Tomasi Italy
Julian Mendez Germany
Oier López de Lacalle Spain
Monica Lestari Paramita United Kingdom
Yannis Marketakis Greece
Chris Hokamp Ireland
Joachim Daiber Netherlands
Dieter Van Uytvanck Netherlands
Maud Ehrmann relative to Petri Leskinen Finland Petri Leskinen's profile →
Citations per field
00.5×6.2×
Petri Leskinen · 1×
Citations per year

Countries citing papers authored by Maud Ehrmann

Since Specialization
Citations

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

Fields of papers citing papers by Maud Ehrmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201295
2 202358
3 201452
4
Building a Multilingual Named Entity-Annotated Corpus Using Annotation Projection
201138
5 202029
6 202125
7
Diachronic Evaluation of NER Systems on Old Newspapers
201623
8 201917
9 201614
10 201912
11 202011
12 202211
13
On Named Entity Recognition in Targeted Twitter Streams in Polish.
20139
14 20209
15 20079
16 20226
17 20095
18 20135
19
Highly Multilingual Coreference Resolution Exploiting a Mature Entity Repository
20114
20 20093

About Maud Ehrmann

Maud Ehrmann is a scholar working on Artificial Intelligence, Literature and Literary Theory, Molecular Biology, Information Systems and Conservation, having authored 38 papers that have together received 460 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (24 papers), Topic Modeling (19 papers), Semantic Web and Ontologies (14 papers), Digital Humanities and Scholarship (6 papers), Web Data Mining and Analysis (4 papers), Advanced Text Analysis Techniques (4 papers), Biomedical Text Mining and Ontologies (4 papers) and Digital and Traditional Archives Management (3 papers). The work is most often cited by research in Artificial Intelligence (364 citations), Conservation (17 citations), Space and Planetary Science (5 citations), Information Systems (76 citations) and Management Science and Operations Research (40 citations). Maud Ehrmann has collaborated with scholars based in Switzerland, France and Italy. Frequent co-authors include Ralf Steinberger, Simon Clematide, Matteo Romanello, Marco Turchi, Antoine Doucet, Elvys Linhares Pontes, Frédé́ric Kaplan, Josef Steinberger, Giovanni Colavizza and Ali Hürriyetoğlu. Their work appears in journals such as Language Resources and Evaluation, Frontiers in Big Data, Semantic Web, Decision Support Systems and ACM Computing Surveys.

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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