Steffen Remus
- Artificial Intelligence top 5%
- Molecular Biology
- Information Systems
- Cognitive Neuroscience
- Computer Vision and Pattern Recognition
- Co-authors
- Chris BiemannOmer LevyIdo DaganStefano FaralliAlexander PanchenkoCédrick FaironSimone Paolo PonzettoLars Kuchinke
- Topics
- Topic Modeling (13 papers)Natural Language Processing Techniques (11 papers)Web Data Mining and Analysis (4 papers)
- Journals
- Language Resources and EvaluationFrontiers in Artificial IntelligenceNorth American Chapter of the Association for Computational Linguistics
In The Last Decade
Steffen Remus
17 papers receiving 250 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 250
- Molecular Biology 30
- Information Systems 26
- Cognitive Neuroscience 13
- Computer Vision and Pattern Recognition 12
Countries citing papers authored by Steffen Remus
This map shows the geographic impact of Steffen Remus'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 Steffen Remus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steffen Remus more than expected).
Fields of papers citing papers by Steffen Remus
This network shows the impact of papers produced by Steffen Remus. 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 Steffen Remus. The network helps show where Steffen Remus may publish in the future.
Co-authorship network of co-authors of Steffen Remus
This figure shows the co-authorship network connecting the top 25 collaborators of Steffen Remus. A scholar is included among the top collaborators of Steffen Remus 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 Steffen Remus. Steffen Remus is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 20 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | Supervised Pun Detection and Location with Feature Engineering and Logistic Regression. | 1 |
| 5 | GermEval 2019 Task 1: Hierarchical Classification of Blurbs. | 1 |
| 6 | Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings | 11 |
| 7 | 59 | |
| 8 | 2 | |
| 9 | WebAnno-MM: EXMARaLDA meets WebAnno | 0 |
| 10 | Retrofitting Word Representations for Unsupervised Sense Aware Word Similarities | 1 |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | Domain-Specific Corpus Expansion with Focused Webcrawling | 2 |
| 15 | 39 | |
| 16 | Top-Level Domain Crawling for Producing Comprehensive Monolingual Corpora from the Web | 1 |
| 17 | 113 | |
| 18 | 3 | |
| 19 | Three Knowledge-Free Methods for Automatic Lexical Chain Extraction | 7 |
About Steffen Remus
Steffen Remus is a scholar working on Artificial Intelligence, Information Systems and Computer Science Applications, having authored 19 papers that have together received 268 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (11 papers) and Web Data Mining and Analysis (4 papers). The work is most often cited by research in Artificial Intelligence (250 citations), Information Systems (26 citations) and Language and Linguistics (8 citations). Steffen Remus has collaborated with scholars based in Germany, Israel and India. Frequent co-authors include Chris Biemann, Omer Levy, Ido Dagan, Stefano Faralli, Alexander Panchenko, Cédrick Fairon, Simone Paolo Ponzetto, Lars Kuchinke, Markus Hofmann and Ralph Radach. Their work appears in journals such as Language Resources and Evaluation, Frontiers in Artificial Intelligence and North American Chapter of the Association for Computational Linguistics.
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.