Katri Haverinen
- Artificial Intelligence top 5%
- Molecular Biology
- Language and Linguistics top 10%
- Computer Vision and Pattern Recognition
- Information Systems
- Co-authors
- Filip GinterJoakim NivreNatalia SilveiraTimothy DozatChristopher D. ManningMarie-Catherine de MarneffeTapio SalakoskiVeronika Laippala
- Topics
- Natural Language Processing Techniques (9 papers)Topic Modeling (8 papers)Text Readability and Simplification (4 papers)
- Journals
- Language Resources and EvaluationDSpace repository (University of Tartu)
In The Last Decade
Katri Haverinen
8 papers receiving 332 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 355
- Molecular Biology 44
- Language and Linguistics 31
- Computer Vision and Pattern Recognition 29
- Information Systems 26
Countries citing papers authored by Katri Haverinen
This map shows the geographic impact of Katri Haverinen'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 Katri Haverinen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katri Haverinen more than expected).
Fields of papers citing papers by Katri Haverinen
This network shows the impact of papers produced by Katri Haverinen. 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 Katri Haverinen. The network helps show where Katri Haverinen may publish in the future.
Co-authorship network of co-authors of Katri Haverinen
This figure shows the co-authorship network connecting the top 25 collaborators of Katri Haverinen. A scholar is included among the top collaborators of Katri Haverinen 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 Katri Haverinen. Katri Haverinen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | Universal Stanford dependencies: A cross-linguistic typology | 255 |
| 3 | Predicting Conjunct Propagation and Other Extended Stanford Dependencies | 11 |
| 4 | Building a Large Automatically Parsed Corpus of Finnish | 1 |
| 5 | 55 | |
| 6 | Towards a Dependency-Based PropBank of General Finnish | 6 |
| 7 | Dependency-Based PropBanking of Clinical Finnish | 10 |
| 8 | Parsing Clinical Finnish: Experiments with Rule-Based and Statistical Dependency Parsers | 7 |
| 9 | 28 |
About Katri Haverinen
Katri Haverinen is a scholar working on Artificial Intelligence, Molecular Biology and Infectious Diseases, having authored 9 papers that have together received 389 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (8 papers) and Text Readability and Simplification (4 papers). The work is most often cited by research in Artificial Intelligence (355 citations), Language and Linguistics (31 citations) and Computer Vision and Pattern Recognition (29 citations). Katri Haverinen has collaborated with scholars based in Finland, Sweden and Pakistan. Frequent co-authors include Filip Ginter, Joakim Nivre, Natalia Silveira, Timothy Dozat, Christopher D. Manning, Marie-Catherine de Marneffe, Tapio Salakoski, Veronika Laippala, Anna Missilä and Stina Ojala. Their work appears in journals such as Language Resources and Evaluation and DSpace repository (University of Tartu).
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.