Ivan Chajda

1.9k citations
272 papers · 1.2k indexed · h-index 17

Impact in

Papers in

Ivan Chajda

214 papers receiving 1.0k citations

Peers

Ivan Chajda
Comparison fields: 5 of 33
  • Computational Theory and Mathematics 1.1k
  • Management Science and Operations Research 618
  • Algebra and Number Theory 227
  • Artificial Intelligence 349
  • Geometry and Topology 71
Replace J. Neggers with:
J. Neggers United States
Radomír Halaš Czechia
P. Corsini Italy
Seok-Zun Song South Korea
Constantine Tsinakis United States
Jiří Rachůnek Czechia
Piergiulio Corsini Italy
R. Ameri Iran
Alden F. Pixley United States
Alan Day Canada
Ivan Chajda relative to J. Neggers United States J. Neggers's profile →
Citations per field
00.5×6.3×
J. Neggers · 1×
Citations per year

Countries citing papers authored by Ivan Chajda

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Chajda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ivan Chajda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ivan Chajda Line = papers co-authored together Ivan Chajda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 272 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200860
2
Congruence classes in universal algebra
200342
3 200829
4 201125
5 199525
6 200122
7 201122
8 199821
9 201221
10 200420
11 197619
12 198919
13
Complemented ordered sets
199218
14 200717
15 200717
16
Lattices and semilattices having an antitone involution in every upper interval
200316
17 201816
18 201216
19
Sheffer Operation in Ortholattices
200515
20 200915

About Ivan Chajda

Ivan Chajda is a scholar working on Computational Theory and Mathematics, Management Science and Operations Research, Artificial Intelligence, Algebra and Number Theory and Geometry and Topology, having authored 272 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Algebra and Logic (240 papers), Rough Sets and Fuzzy Logic (111 papers), Fuzzy and Soft Set Theory (88 papers), Logic, Reasoning, and Knowledge (67 papers), Rings, Modules, and Algebras (38 papers), Advanced Topics in Algebra (23 papers), semigroups and automata theory (22 papers) and Multi-Criteria Decision Making (12 papers). The work is most often cited by research in Computational Theory and Mathematics (1.1k citations), Management Science and Operations Research (618 citations), Algebra and Number Theory (227 citations), Artificial Intelligence (349 citations) and Geometry and Topology (71 citations). Ivan Chajda has collaborated with scholars based in Czechia, Austria and Italy. Frequent co-authors include Helmut Länger, Radomír Halaš, Jan Kühr, Bohdan Zelinka, Jan Paseka, Jiří Rachůnek, Václav Snåšel, Gábor Czédli, Antonio Ledda and Ivo G. Rosenberg. Their work appears in journals such as Soft Computing, Fuzzy Sets and Systems, Logic Journal of IGPL, Discrete Mathematics and Mathematica Slovaca.

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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