Jakub Zavrel
- Artificial Intelligence top 2%
- Information Systems top 10%
- Language and Linguistics top 5%
- Computer Vision and Pattern Recognition
- Molecular Biology
- Co-authors
- Walter DaelemansAntal van den BoschHans van HalterenSteven GillisJorn VeenstraFrank Van EyndeTomaž ErjavecSašo Džeroski
- Topics
- Natural Language Processing Techniques (24 papers)Topic Modeling (18 papers)Speech and dialogue systems (13 papers)
- Partner nations
- NetherlandsBelgiumSlovenia
In The Last Decade
Jakub Zavrel
31 papers receiving 637 citations
Peers
Comparison fields: 5 of 52
- Artificial Intelligence 752
- Information Systems 78
- Language and Linguistics 63
- Computer Vision and Pattern Recognition 49
- Molecular Biology 37
Countries citing papers authored by Jakub Zavrel
This map shows the geographic impact of Jakub Zavrel'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 Jakub Zavrel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jakub Zavrel more than expected).
Fields of papers citing papers by Jakub Zavrel
This network shows the impact of papers produced by Jakub Zavrel. 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 Jakub Zavrel. The network helps show where Jakub Zavrel may publish in the future.
Co-authorship network of co-authors of Jakub Zavrel
This figure shows the co-authorship network connecting the top 25 collaborators of Jakub Zavrel. A scholar is included among the top collaborators of Jakub Zavrel 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 Jakub Zavrel. Jakub Zavrel 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 | DAESO Corpus: Parallel Dutch Monolingual Treebank | 1 |
| 3 | 0 | |
| 4 | Learning to Compose Effective Strategies from a Library of Dialogue Components | 0 |
| 5 | MBT : Memory Based Tagger, version 1.0, Reference Guide | 16 |
| 6 | Proceedings of the Computational Linguistics in the Netherlands | 11 |
| 7 | Morphosyntactic Tagging of Slovene: Evaluating Taggers and Tagsets. | 17 |
| 8 | Unpacking Multi-valued Symbolic Features and Classes in Memory-Based Language Learning | 3 |
| 9 | Part of speech tagging and lemmatisation for the spoken Dutch corpus | 19 |
| 10 | Diverse classifiers for NLP disambiguation tasks: comparisons, optimization, combination, and evolution | 2 |
| 11 | 3 | |
| 12 | Lemmatisation and morphosyntactic annotation for the spoken Dutch corpus | 3 |
| 13 | TIMBL : Tilburg Memory-Based Learner. Version 1.0, Reference Guide | 34 |
| 14 | 69 | |
| 15 | 6 | |
| 16 | An Empirical Re-Examination of Weighted Voting for k-NN | 10 |
| 17 | Resolving PP attachment Ambiguities with Memory-Based Learning | 34 |
| 18 | A feature-relevance heuristic for indexing and compressing large case bases | 6 |
| 19 | 15 | |
| 20 | Memory-Based Part of Speech tagging | 3 |
About Jakub Zavrel
Jakub Zavrel is a scholar working on Artificial Intelligence, Information Systems and Information Systems and Management, having authored 35 papers that have together received 802 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (24 papers), Topic Modeling (18 papers) and Speech and dialogue systems (13 papers). The work is most often cited by research in Artificial Intelligence (752 citations), Language and Linguistics (63 citations) and Information Systems (78 citations). Jakub Zavrel has collaborated with scholars based in Netherlands, Belgium and Slovenia. Frequent co-authors include Walter Daelemans, Antal van den Bosch, Hans van Halteren, Steven Gillis, Jorn Veenstra, Frank Van Eynde, Tomaž Erjavec, Sašo Džeroski, Khalil Sima’an and Sabine Buchholz. Their work appears in journals such as Machine Learning, Artificial Intelligence Review and 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.