Citations per year, relative to Sámi Virpioja Sámi Virpioja (= 1×)
peers
Mathias Creutz
Countries citing papers authored by Sámi Virpioja
Since
Specialization
Citations
This map shows the geographic impact of Sámi Virpioja'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 Sámi Virpioja with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sámi Virpioja more than expected).
This network shows the impact of papers produced by Sámi Virpioja. 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 Sámi Virpioja. The network helps show where Sámi Virpioja may publish in the future.
Co-authorship network of co-authors of Sámi Virpioja
This figure shows the co-authorship network connecting the top 25 collaborators of Sámi Virpioja.
A scholar is included among the top collaborators of Sámi Virpioja 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 Sámi Virpioja. Sámi Virpioja is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Grönroos, Stig-Arne, Sámi Virpioja, Peter Smit, & Mikko Kurimo. (2014). Morfessor FlatCat: An HMM-Based Method for Unsupervised and Semi-Supervised Learning of Morphology. International Conference on Computational Linguistics. 1177–1185.47 indexed citations
11.
Virpioja, Sámi, et al.. (2013). Supervised Morphological Segmentation in a Low-Resource Learning Setting using Conditional Random Fields. 29–37.31 indexed citations
12.
Virpioja, Sámi, et al.. (2011). Evaluating the effect of word frequencies in a probabilistic generative model of morphology. DSpace repository (University of Tartu). 230–237.6 indexed citations
13.
Virpioja, Sámi, et al.. (2011). Empirical Comparison of Evaluation Methods for Unsupervised Learning of Morphology. 52(2). 45–90.31 indexed citations
14.
Kurimo, Mikko, Sámi Virpioja, Ville Turunen, & Krista Lagus. (2010). Morpho Challenge competition 2005--2010: evaluations and results. Meeting of the Association for Computational Linguistics. 87–95.20 indexed citations
15.
Kurimo, Mikko, Sámi Virpioja, Ville Turunen, & Krista Lagus. (2010). Morpho Challenge 2005-2010: Evaluations and Results. Meeting of the Association for Computational Linguistics. 87–95.17 indexed citations
16.
Vatanen, Tommi, et al.. (2010). Language identification of short text segments with n-gram models. Language Resources and Evaluation.58 indexed citations
17.
Virpioja, Sámi, et al.. (2010). Semi-Supervised Learning of Concatenative Morphology. Meeting of the Association for Computational Linguistics. 78–86.41 indexed citations
18.
Virpioja, Sámi, et al.. (2010). Applying Morphological Decompositions to Statistical Machine Translation. Workshop on Statistical Machine Translation. 195–200.3 indexed citations
19.
Virpioja, Sámi, et al.. (2009). Unsupervised Morpheme Discovery with Allomorfessor.. CLEF (Working Notes).4 indexed citations
20.
Creutz, Mathias, Krista Lagus, Krister Lindén, & Sámi Virpioja. (2005). Morfessor and Hutmegs : Unsupervised Morpheme Segmentation for Highly-Inflecting and Compounding Languages. Työväentutkimus Vuosikirja.16 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.