Johannes Knopp
- Artificial Intelligence top 5%
- Information Systems top 10%
- Computer Vision and Pattern Recognition
- Molecular Biology
- Communication
- Topics
- Natural Language Processing Techniques (5 papers)Topic Modeling (4 papers)Wikis in Education and Collaboration (2 papers)
- Journals
- Language Resources and EvaluationRepository KITopen (Karlsruhe Institute of Technology)MADOC (University of Mannheim)
- Partner nations
- Germany
In The Last Decade
Johannes Knopp
5 papers receiving 425 citations
Hit Papers
Peers
Comparison fields: 5 of 65
- Artificial Intelligence 345
- Information Systems 71
- Computer Vision and Pattern Recognition 46
- Molecular Biology 28
- Communication 27
Countries citing papers authored by Johannes Knopp
This map shows the geographic impact of Johannes Knopp'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 Johannes Knopp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johannes Knopp more than expected).
Fields of papers citing papers by Johannes Knopp
This network shows the impact of papers produced by Johannes Knopp. 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 Johannes Knopp. The network helps show where Johannes Knopp may publish in the future.
Co-authorship network of co-authors of Johannes Knopp
This figure shows the co-authorship network connecting the top 25 collaborators of Johannes Knopp. A scholar is included among the top collaborators of Johannes Knopp 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 Johannes Knopp. Johannes Knopp is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | Extending a multilingual Lexical Resource by bootstrapping Named Entity Classification using Wikipedia's Category System | 3 |
| 3 | Classification of Named Entities in a large multilingual resource using the Wikipedia category system | 2 |
| 4 | Building a Multilingual Lexical Resource for Named Entity Recognition and Translation and Transliteration | 0 |
| 5 | Building a Multilingual Lexical Resource for Named Entity Disambiguation, Translation and Transliteration | 31 |
| 6 | Proceedings of the International Conference on Language Resources and Evaluation (LREC)breakdown → | 403 |
About Johannes Knopp
Johannes Knopp is a scholar working on Museology, Communication and Artificial Intelligence, having authored 6 papers that have together received 441 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (5 papers), Topic Modeling (4 papers) and Wikis in Education and Collaboration (2 papers). The work is most often cited by research in Artificial Intelligence (345 citations), Communication (27 citations) and Information Systems (71 citations). Johannes Knopp has collaborated with scholars based in Germany. Frequent co-authors include Carina Silberer, Matthias Härtung and Peter Bamberger. Their work appears in journals such as Language Resources and Evaluation, Repository KITopen (Karlsruhe Institute of Technology) and MADOC (University of Mannheim).
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.