Maud Ehrmann

925 total citations
30 papers, 311 citations indexed

About

Maud Ehrmann is a scholar working on Artificial Intelligence, Literature and Literary Theory and Molecular Biology. According to data from OpenAlex, Maud Ehrmann has authored 30 papers receiving a total of 311 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 5 papers in Literature and Literary Theory and 4 papers in Molecular Biology. Recurrent topics in Maud Ehrmann's work include Natural Language Processing Techniques (18 papers), Semantic Web and Ontologies (13 papers) and Topic Modeling (13 papers). Maud Ehrmann is often cited by papers focused on Natural Language Processing Techniques (18 papers), Semantic Web and Ontologies (13 papers) and Topic Modeling (13 papers). Maud Ehrmann collaborates with scholars based in Switzerland, Italy and France. Maud Ehrmann's co-authors include Ralf Steinberger, Marco Turchi, Matteo Romanello, Josef Steinberger, Guillaume Jacquet, Mijail Kabadjov, Ali Hürriyetoğlu, Roberto Navigli, Vanni Zavarella and Daniele Vannella and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACM Computing Surveys and Decision Support Systems.

In The Last Decade

Maud Ehrmann

26 papers receiving 266 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Maud Ehrmann Switzerland 9 253 49 41 27 15 30 311
Ulli Waltinger Germany 10 226 0.9× 35 0.7× 25 0.6× 13 0.5× 17 1.1× 30 267
Osma Suominen Finland 9 218 0.9× 88 1.8× 21 0.5× 42 1.6× 40 2.7× 27 265
Pavel Braslavski Russia 9 180 0.7× 80 1.6× 20 0.5× 16 0.6× 12 0.8× 43 260
Rahul Bhagat United States 9 380 1.5× 55 1.1× 35 0.9× 21 0.8× 27 1.8× 14 412
Kalliopi Zervanou Netherlands 8 163 0.6× 34 0.7× 16 0.4× 7 0.3× 35 2.3× 31 209
Itziar Aldabe Spain 8 296 1.2× 65 1.3× 22 0.5× 42 1.6× 32 2.1× 30 329
Stephen Tratz United States 12 370 1.5× 35 0.7× 38 0.9× 18 0.7× 33 2.2× 33 430
Nuno Freire Portugal 7 110 0.4× 84 1.7× 16 0.4× 13 0.5× 10 0.7× 32 208
Pavel Straňák Czechia 8 368 1.5× 32 0.7× 39 1.0× 12 0.4× 28 1.9× 20 399
Stephan Gouws South Africa 8 449 1.8× 44 0.9× 70 1.7× 6 0.2× 12 0.8× 9 484

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-authorship network of co-authors of Maud Ehrmann

This figure shows the co-authorship network connecting the top 25 collaborators of Maud Ehrmann. A scholar is included among the top collaborators of Maud Ehrmann 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 Maud Ehrmann. Maud Ehrmann 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
1.
Romanello, Matteo, et al.. (2023). impresso Text Reuse at Scale. An interface for the exploration of text reuse data in semantically enriched historical newspapers. Frontiers in Big Data. 6. 1249469–1249469. 1 indexed citations
2.
Ehrmann, Maud, et al.. (2023). Named Entity Recognition and Classification in Historical Documents: A Survey. ACM Computing Surveys. 56(2). 1–47. 37 indexed citations
3.
Ehrmann, Maud, et al.. (2022). ECCE: Entity-centric Corpus Exploration Using Contextual Implicit Networks. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 278–281. 1 indexed citations
4.
Ehrmann, Maud, et al.. (2021). Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers. Zurich Open Repository and Archive (University of Zurich). 15 indexed citations
5.
Ehrmann, Maud, et al.. (2020). Language Resources for Historical Newspapers: the Impresso Collection. Language Resources and Evaluation. 958–968. 7 indexed citations
6.
Ehrmann, Maud, et al.. (2019). Historical Newspaper User Interfaces: A Review. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1–24. 12 indexed citations
7.
Colavizza, Giovanni, et al.. (2019). The Past, Present and Future of Digital Scholarship with Newspaper Collections. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1 indexed citations
8.
Jacquet, Guillaume, et al.. (2016). Cross-lingual Linking of Multi-word Entities and their corresponding Acronyms. Language Resources and Evaluation. 528–535. 1 indexed citations
9.
Ehrmann, Maud, et al.. (2016). Diachronic Evaluation of NER Systems on Old Newspapers. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 97–107. 14 indexed citations
10.
Jacquet, Guillaume, et al.. (2016). European Media Monitor. Joint Research Centre (European Commission). 1 indexed citations
11.
Ehrmann, Maud, et al.. (2016). Navigating through 200 years of historical newspapers. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1 indexed citations
12.
Colavizza, Giovanni, et al.. (2016). A Method for Record Linkage with Sparse Historical Data. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 463–466. 1 indexed citations
13.
Ehrmann, Maud, et al.. (2016). From Documents to Structured Data: First Milestones of the Garzoni Project. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2016(2).
14.
Jacquet, Guillaume, Maud Ehrmann, & Ralf Steinberger. (2014). Clustering of Multi-Word Named Entity variants: Multilingual Evaluation. Language Resources and Evaluation. 2548–2553. 2 indexed citations
15.
Ehrmann, Maud, Francesco Cecconi, Daniele Vannella, et al.. (2014). Representing Multilingual Data as Linked Data: the Case of BabelNet 2.0. Language Resources and Evaluation. 401–408. 42 indexed citations
16.
Steinberger, Ralf, et al.. (2014). Media monitoring and information extraction for the highly inflected agglutinative language Hungarian. Language Resources and Evaluation. 2049–2056. 2 indexed citations
17.
Piskorski, Jakub & Maud Ehrmann. (2013). On Named Entity Recognition in Targeted Twitter Streams in Polish.. Meeting of the Association for Computational Linguistics. 84–93. 8 indexed citations
18.
Steinberger, Josef, Maud Ehrmann, Ali Hürriyetoğlu, et al.. (2012). Creating sentiment dictionaries via triangulation. Decision Support Systems. 53(4). 689–694. 82 indexed citations
19.
Ehrmann, Maud, Marco Turchi, & Ralf Steinberger. (2011). Building a Multilingual Named Entity-Annotated Corpus Using Annotation Projection. Recent Advances in Natural Language Processing. 118–124. 34 indexed citations
20.
Steinberger, Josef, et al.. (2011). Highly Multilingual Coreference Resolution Exploiting a Mature Entity Repository. Recent Advances in Natural Language Processing. 254–260. 4 indexed citations

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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