Johann Roturier
- Artificial Intelligence top 5%
- Information Systems top 10%
- Language and Linguistics top 5%
- Sociology and Political Science
- Communication
- Co-authors
- Andy WayPhilipp KoehnMarko TadićSharon O’BrienJosef van GenabithLinda MitchellJennifer FosterRaphaël Rubino
- Topics
- Natural Language Processing Techniques (32 papers)Topic Modeling (27 papers)Text Readability and Simplification (9 papers)
- Journals
- Machine TranslationWolverhampton Intellectual Repository and E-Theses (University of Wolverhampton)Arrow@dit (Dublin Institute of Technology)
- Partner nations
- IrelandUnited StatesSwitzerland
In The Last Decade
Johann Roturier
35 papers receiving 325 citations
Peers
Comparison fields: 5 of 49
- Artificial Intelligence 297
- Information Systems 68
- Language and Linguistics 60
- Sociology and Political Science 38
- Communication 22
Countries citing papers authored by Johann Roturier
This map shows the geographic impact of Johann Roturier'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 Johann Roturier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johann Roturier more than expected).
Fields of papers citing papers by Johann Roturier
This network shows the impact of papers produced by Johann Roturier. 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 Johann Roturier. The network helps show where Johann Roturier may publish in the future.
Co-authorship network of co-authors of Johann Roturier
This figure shows the co-authorship network connecting the top 25 collaborators of Johann Roturier. A scholar is included among the top collaborators of Johann Roturier 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 Johann Roturier. Johann Roturier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 43 | |
| 3 | Localizing Apps: A practical guide for translators and translation students | 9 |
| 4 | Quality Estimation of English-French Machine Translation: A Detailed Study of the Role of Syntax | 5 |
| 5 | Proceedings of the 17th Annual Conference of the European Association for Machine Translation | 83 |
| 6 | Using the ACCEPT framework to conduct an online community-based translation evaluation study | 1 |
| 7 | 1 | |
| 8 | Estimating the Quality of Translated User-Generated Content | 6 |
| 9 | DCU-Symantec at the WMT 2013 Quality Estimation Shared Task | 6 |
| 10 | Parser Accuracy in Quality Estimation of Machine Translation: A Tree Kernel Approach | 3 |
| 11 | The ACCEPT post-editing environment: a flexible and customisable online tool to perform and analyse machine translation post-editing. | 8 |
| 12 | Translation Quality-Based Supplementary Data Selection by Incremental Update of Translation Models | 8 |
| 13 | Using Automatic Machine Translation Metrics to Analyze the Impact of Source Reformulations. | 6 |
| 14 | DCU-Symantec Submission for the WMT 2012 Quality Estimation Task | 15 |
| 15 | The DCU machine translation systems for IWSLT 2011. | 1 |
| 16 | Domain Adaptation in Statistical Machine Translation of User-Forum Data using Component Level Mixture Modelling. | 15 |
| 17 | Evaluation of MT Systems to Translate User Generated Content | 17 |
| 18 | Improving the post-editing experience using translation recommendation: a user study | 13 |
| 19 | TMX Markup: A Challenge When Adapting SMT to the Localisation Environment | 6 |
| 20 | Postediting Machine Translation Output Guidelines | 1 |
About Johann Roturier
Johann Roturier is a scholar working on Artificial Intelligence, Information Systems and Language and Linguistics, having authored 37 papers that have together received 377 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (32 papers), Topic Modeling (27 papers) and Text Readability and Simplification (9 papers). The work is most often cited by research in Artificial Intelligence (297 citations), Language and Linguistics (60 citations) and Communication (22 citations). Johann Roturier has collaborated with scholars based in Ireland, United States and Switzerland. Frequent co-authors include Andy Way, Philipp Koehn, Marko Tadić, Sharon O’Brien, Josef van Genabith, Linda Mitchell, Jennifer Foster, Raphaël Rubino, Sudip Kumar Naskar and Florian Schaub. Their work appears in journals such as Machine Translation, Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton) and Arrow@dit (Dublin Institute of Technology).
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.