This map shows the geographic impact of Tomaž Erjavec'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 Tomaž Erjavec with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomaž Erjavec more than expected).
This network shows the impact of papers produced by Tomaž Erjavec. 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 Tomaž Erjavec. The network helps show where Tomaž Erjavec may publish in the future.
Co-authorship network of co-authors of Tomaž Erjavec
This figure shows the co-authorship network connecting the top 25 collaborators of Tomaž Erjavec.
A scholar is included among the top collaborators of Tomaž Erjavec 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 Tomaž Erjavec. Tomaž Erjavec is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Krek, Simon, et al.. (2020). Gigafida 2.0: The Reference Corpus of Written Standard Slovene. Language Resources and Evaluation. 3340–3345.6 indexed citations
Krek, Simon, et al.. (2018). Leksikon besednih oblik Sloleks in smernice njegovega razvoja.2 indexed citations
6.
Ljubešić, Nikola, Tomaž Erjavec, & Darja Fišer. (2016). Corpus-Based Diacritic Restoration for South Slavic Languages.. Language Resources and Evaluation. 3612–3616.9 indexed citations
7.
Erjavec, Tomaž, et al.. (2016). Gold-Standard Datasets for Annotation of Slovene Computer-Mediated Communication.. 29–40.3 indexed citations
8.
Ljubešić, Nikola & Tomaž Erjavec. (2016). Corpus vs. Lexicon Supervision in Morphosyntactic Tagging: the Case of Slovene. Language Resources and Evaluation. 1527–1531.15 indexed citations
9.
Ljubešić, Nikola, et al.. (2016). Normalising Slovene data: historical texts vs. user-generated content..20 indexed citations
10.
Podpečan, Vid, Tomaž Erjavec, Senja Pollak, et al.. (2015). Text mining platform for NLP workflow design, replication and reuse. Lirias (KU Leuven).2 indexed citations
11.
Erjavec, Tomaž. (2012). The goo300k corpus of historical Slovene. Language Resources and Evaluation. 2257–2260.5 indexed citations
12.
Erjavec, Tomaž, et al.. (2011). OD BIOGRAFSKEGA LEKSIKONA DO ZNANSTVENOKRITIČNE IZDAJE: VPRAŠANJE TRAJNOSTI ELEKTRONSKIH BESEDIL. 55(1).
13.
Sharoff, Serge, et al.. (2008). Designing and evaluating a Russian tagset. Language Resources and Evaluation. 279–285.28 indexed citations
14.
Erjavec, Tomaž, et al.. (2008). A Low Cost Approach to Building a Japanese-Slovene Parallel Corpus. IEICE Technical Report; IEICE Tech. Rep.. 108(50). 7–10.2 indexed citations
15.
Erjavec, Tomaž & Simon Krek. (2008). The JOS Morphosyntactically Tagged Corpus of Slovene. Language Resources and Evaluation.8 indexed citations
16.
Erjavec, Tomaž. (2002). Compiling and Using the IJS-ELAN Parallel Corpus.. Informatica (slovenia). 26.3 indexed citations
17.
Ide, Nancy, Tomaž Erjavec, & Dan Tufiş. (2001). Automatic Sense Tagging Using Parallel Corpora.. 83–90.18 indexed citations
18.
Džeroski, Sašo, Tomaž Erjavec, & Jakub Zavrel. (2000). Morphosyntactic Tagging of Slovene: Evaluating Taggers and Tagsets.. Language Resources and Evaluation.17 indexed citations
19.
Erjavec, Tomaž & Nancy Ide. (1998). The MULTEXT-East Corpus. Language Resources and Evaluation. 971–974.27 indexed citations
20.
Erjavec, Tomaž, Ann Marie Lawson, & Laurent Romary. (1998). East meets West: Producing Multilingual Resources in a European Context. Language Resources and Evaluation.8 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
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Rankless may not fully capture the entirety of a scholar's output or impact.