Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Filip Ginter'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 Filip Ginter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Filip Ginter more than expected).
This network shows the impact of papers produced by Filip Ginter. 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 Filip Ginter. The network helps show where Filip Ginter may publish in the future.
Co-authorship network of co-authors of Filip Ginter
This figure shows the co-authorship network connecting the top 25 collaborators of Filip Ginter.
A scholar is included among the top collaborators of Filip Ginter 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 Filip Ginter. Filip Ginter is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tiedemann, Jörg, et al.. (2020). The FISKMÖ Project: Resources and Tools for Finnish-Swedish Machine Translation and Cross-Linguistic Research. Language Resources and Evaluation. 3808–3815.3 indexed citations
5.
Nivre, Joakim, Marie-Catherine de Marneffe, Filip Ginter, et al.. (2020). Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection. KTH Publication Database DiVA (KTH Royal Institute of Technology). 4034–4043.8 indexed citations
Zeman, Daniel, Jan Hajič, Martin Popel, et al.. (2018). CoNLL 2018 Shared Task : Multilingual Parsing from Raw Text to Universal Dependencies. 1–21.96 indexed citations
8.
Ginter, Filip, et al.. (2018). Återanvändningen av text i den finska tidningspressen 1771–1853. 103(1).1 indexed citations
Marneffe, Marie-Catherine de, Timothy Dozat, Natalia Silveira, et al.. (2014). Universal Stanford dependencies: A cross-linguistic typology. Language Resources and Evaluation. 4585–4592.255 indexed citations
14.
Hakala, Kai, Sofie Van Landeghem, Tapio Salakoski, Yves Van de Peer, & Filip Ginter. (2013). EVEX in ST'13: Application of a large-scale text mining resource to event extraction and network construction. Meeting of the Association for Computational Linguistics. 26–34.32 indexed citations
15.
Björne, Jari, Sofie Van Landeghem, Sampo Pyysalo, et al.. (2012). PubMed-Scale Event Extraction for Post-Translational Modifications, Epigenetics and Protein Structural Relations. Research Explorer (The University of Manchester). 82–90.9 indexed citations
16.
Landeghem, Sofie Van, Filip Ginter, Yves Van de Peer, & Tapio Salakoski. (2011). EVEX: A PubMed-Scale Resource for Homology-Based Generalization of Text Mining Predictions. Ghent University Academic Bibliography (Ghent University). 28–37.26 indexed citations
17.
Haverinen, Katri, et al.. (2010). Dependency-Based PropBanking of Clinical Finnish. 137–141.10 indexed citations
18.
Salakoski, Tapio, et al.. (2006). Advances in Natural Language Processing: 5th International Conference, FinTAL 2006 Turku, Finland, August 23-25, 2006 Proceedings (Lecture Notes in Computer Science). Springer eBooks.2 indexed citations
19.
Salakoski, Tapio, et al.. (2006). Advances in natural language processing : 5th International Conference on NLP, FinTAL 2006, Turku, Finland, August 23-25, 2006 : proceedings. Springer eBooks.2 indexed citations
20.
Pahikkala, Tapio, Sampo Pyysalo, Filip Ginter, et al.. (2005). Kernels Incorporating Word Positional Information in Natural Language Disambiguation Tasks.. The Florida AI Research Society. 442–448.9 indexed citations
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.