Tomáš Kliegr

727 total citations
46 papers, 287 citations indexed

About

Tomáš Kliegr is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics. According to data from OpenAlex, Tomáš Kliegr has authored 46 papers receiving a total of 287 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 14 papers in Information Systems and 9 papers in Computational Theory and Mathematics. Recurrent topics in Tomáš Kliegr's work include Topic Modeling (13 papers), Natural Language Processing Techniques (13 papers) and Semantic Web and Ontologies (12 papers). Tomáš Kliegr is often cited by papers focused on Topic Modeling (13 papers), Natural Language Processing Techniques (13 papers) and Semantic Web and Ontologies (12 papers). Tomáš Kliegr collaborates with scholars based in Czechia, United Kingdom and Germany. Tomáš Kliegr's co-authors include Johannes Fürnkranz, Štěpán Bahník, Ebroul Izquierdo, Vojtěch Svátek, Ondřej Zamazal, Krishna Chandramouli, Martin Atzmueller, Ute Schmid, Ian Johnson and Michael Hahsler and has published in prestigious journals such as Artificial Intelligence, Machine Learning and Knowledge-Based Systems.

In The Last Decade

Tomáš Kliegr

40 papers receiving 280 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tomáš Kliegr Czechia	10	173	44	33	22	17	46	287
Marco Fisichella Germany	11	179 1.0×	54 1.2×	42 1.3×	35 1.6×	9 0.5×	44	313
Nadin Kökciyan United Kingdom	10	233 1.3×	58 1.3×	27 0.8×	18 0.8×	10 0.6×	41	327
Ilia Shumailov United Kingdom	8	188 1.1×	68 1.5×	38 1.2×	9 0.4×	33 1.9×	19	396
Minje Choi South Korea	4	164 0.9×	40 0.9×	61 1.8×	7 0.3×	26 1.5×	12	325
Rishi Bommasani United States	7	330 1.9×	40 0.9×	36 1.1×	18 0.8×	59 3.5×	15	435
Marianne Cherrington New Zealand	8	67 0.4×	31 0.7×	18 0.5×	17 0.8×	8 0.5×	27	229
Reid Pryzant United States	11	324 1.9×	53 1.2×	76 2.3×	18 0.8×	11 0.6×	15	448
Katherine Lee United States	7	265 1.5×	55 1.3×	42 1.3×	23 1.0×	42 2.5×	13	375
Georgios Kontonatsios United Kingdom	11	224 1.3×	50 1.1×	23 0.7×	12 0.5×	30 1.8×	23	422
Niklas Muennighoff United States	6	302 1.7×	37 0.8×	55 1.7×	16 0.7×	15 0.9×	8	379

Countries citing papers authored by Tomáš Kliegr

Since Specialization

Citations

This map shows the geographic impact of Tomáš Kliegr'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 Tomáš Kliegr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomáš Kliegr more than expected).

Fields of papers citing papers by Tomáš Kliegr

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tomáš Kliegr. 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 Tomáš Kliegr. The network helps show where Tomáš Kliegr may publish in the future.

Co-authorship network of co-authors of Tomáš Kliegr

This figure shows the co-authorship network connecting the top 25 collaborators of Tomáš Kliegr. A scholar is included among the top collaborators of Tomáš Kliegr 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 Tomáš Kliegr. Tomáš Kliegr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Kliegr, Tomáš, et al.. (2025). Explainable rule-based prediction of cultivation media for microbes. Computational and Structural Biotechnology Journal. 27. 5194–5206.

2.

Kliegr, Tomáš, et al.. (2025). Traceable LLM-based validation of statements in knowledge graphs. Information Processing & Management. 62(4). 104128–104128. 2 indexed citations

3.

Atzmueller, Martin, Johannes Fürnkranz, Tomáš Kliegr, & Ute Schmid. (2024). Explainable and interpretable machine learning and data mining. Data Mining and Knowledge Discovery. 38(5). 2571–2595. 18 indexed citations

4.

Kliegr, Tomáš & Ebroul Izquierdo. (2023). QCBA: improving rule classifiers learned from quantitative data by recovering information lost by discretisation. Applied Intelligence. 53(18). 20797–20827. 5 indexed citations

5.

Joachimiak, Marcin P., et al.. (2022). Why was this cited? Explainable machine learning applied to COVID-19 research literature. Scientometrics. 127(5). 2313–2349. 12 indexed citations

6.

Kliegr, Tomáš, et al.. (2022). Role of population and test characteristics in antigen-based SARS-CoV-2 diagnosis, Czechia, August to November 2021. Eurosurveillance. 27(33). 4 indexed citations

7.

Kliegr, Tomáš, et al.. (2020). Action Rules: Counterfactual Explanations in Python.. 28–41. 1 indexed citations

8.

Gutiérrez-Basulto, Víctor, et al.. (2020). Rules and Reasoning. Lecture notes in computer science. 1 indexed citations

9.

Kliegr, Tomáš, et al.. (2019). Tuning Hyperparameters of Classification Based on Associations (CBA).. 9–16. 3 indexed citations

10.

Filip, Jiřı́ & Tomáš Kliegr. (2019). PyIDS - Python Implementation of Interpretable Decision Sets Algorithm by Lakkaraju et al, 2016.. 2 indexed citations

11.

Kliegr, Tomáš, et al.. (2017). Outlier (Anomaly) Detection Modelling in PMML..

12.

Kliegr, Tomáš, et al.. (2017). EasyMiner - Short History of Research and Current Development.. 235–239. 2 indexed citations

13.

Zeman, Václav, et al.. (2017). Using EasyMiner API for Financial Data Analysis in the OpenBudgets.eu Project..

14.

Kliegr, Tomáš. (2017). Quantitative CBA: Small and Comprehensible Association Rule Classification Models.. arXiv (Cornell University). 1 indexed citations

15.

Kliegr, Tomáš, et al.. (2016). Crowdsourced Corpus with Entity Salience Annotations. Language Resources and Evaluation. 3307–3311. 7 indexed citations

16.

Kliegr, Tomáš, et al.. (2014). InBeat: Recommender System as a Service.. CLEF (Working Notes). 837–844.

17.

Kliegr, Tomáš & Ondřej Zamazal. (2014). Towards Linked Hypernyms Dataset 2.0: complementing DBpedia with hypernym discovery. Language Resources and Evaluation. 3517–3523. 4 indexed citations

18.

Kliegr, Tomáš, et al.. (2013). Wikipedia Search as Effective Entity Linking Algorithm.. Theory and applications of categories. 2 indexed citations

19.

Kliegr, Tomáš, et al.. (2013). Transforming Association Rules to Business Rules: EasyMiner meets Drools.. 3 indexed citations

20.

Kliegr, Tomáš, et al.. (2010). SEWEBAR-CMS: A System for Postprocessing Data Mining Models.. 1 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.

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