Jan Kühr
- Computational Theory and Mathematics top 2%
- Management Science and Operations Research top 5%
- Artificial Intelligence top 10%
- Algebra and Number Theory
- Geometry and Topology
- Co-authors
- Ivan ChajdaRadomír HalašDaniele MundiciAnatolij DvurečenskijLavinia Corina CiunguLianzhen LiuConstantine TsinakisJiří Rachůnek
- Topics
- Advanced Algebra and Logic (41 papers)Rough Sets and Fuzzy Logic (30 papers)Fuzzy and Soft Set Theory (27 papers)
- Cited by
- Computational Theory and MathematicsManagement Science and Operations ResearchAlgebra and Number Theory
- Partner nations
- CzechiaUnited StatesItaly
In The Last Decade
Jan Kühr
38 papers receiving 311 citations
Peers
Comparison fields: 5 of 14
- Computational Theory and Mathematics 323
- Management Science and Operations Research 200
- Artificial Intelligence 128
- Algebra and Number Theory 20
- Geometry and Topology 5
Countries citing papers authored by Jan Kühr
This map shows the geographic impact of Jan Kühr'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 Jan Kühr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Kühr more than expected).
Fields of papers citing papers by Jan Kühr
This network shows the impact of papers produced by Jan Kühr. 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 Jan Kühr. The network helps show where Jan Kühr may publish in the future.
Co-authorship network of co-authors of Jan Kühr
This figure shows the co-authorship network connecting the top 25 collaborators of Jan Kühr. A scholar is included among the top collaborators of Jan Kühr 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 Jan Kühr. Jan Kühr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 2 | |
| 3 | Basic algebras (Clone Theory and Discrete Mathematics・Algebra and Logic Related to Computer Science) | 3 |
| 4 | 1 | |
| 5 | 13 | |
| 6 | A System-On-Chip Platform for HRTF-Based Realtime Spatial Audio Rendering | 1 |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 5 | |
| 10 | 16 | |
| 11 | 1 | |
| 12 | 46 | |
| 13 | 14 | |
| 14 | 2 | |
| 15 | Finite-valued dually residuated lattice-ordered monoids | 1 |
| 16 | On a Generalization of Pseudo MV-Algebras Quasi-matrix Logic. | 2 |
| 17 | 14 | |
| 18 | 0 | |
| 19 | 23 | |
| 20 | Prime ideals and polars in DR$\ell $-monoids and BL-algebras | 5 |
About Jan Kühr
Jan Kühr is a scholar working on Computational Theory and Mathematics, Management Science and Operations Research and Algebra and Number Theory, having authored 43 papers that have together received 328 indexed citations. Recurring topics across this work include Advanced Algebra and Logic (41 papers), Rough Sets and Fuzzy Logic (30 papers) and Fuzzy and Soft Set Theory (27 papers). The work is most often cited by research in Computational Theory and Mathematics (323 citations), Management Science and Operations Research (200 citations) and Algebra and Number Theory (20 citations). Jan Kühr has collaborated with scholars based in Czechia, United States and Italy. Frequent co-authors include Ivan Chajda, Radomír Halaš, Daniele Mundici, Anatolij Dvurečenskij, Lavinia Corina Ciungu, Lianzhen Liu, Constantine Tsinakis, Jiří Rachůnek, Jürgen Reichardt and Jan Paseka. Their work appears in journals such as Fuzzy Sets and Systems, Soft Computing and Journal of Algebra.
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.