Young-Bae Jun

890 citations
87 papers · 557 indexed · h-index 13

Impact in

Papers in

Young-Bae Jun

66 papers receiving 447 citations

Peers

Young-Bae Jun
Comparison fields: 5 of 27
  • Management Science and Operations Research 432
  • Computational Theory and Mathematics 415
  • Algebra and Number Theory 71
  • Geometry and Topology 61
  • Artificial Intelligence 210
Replace Naseem Ajmal with:
Naseem Ajmal India
Violeta Leoreanu Romania
Thomas Vetterlein Austria
Bin Zhao China
K. P. Shum China
Radomír Halaš Czechia
R. Ameri Iran
Hashem Bordbar Slovenia
Stojan Bogdanović Serbia
Liu Wang-jin China
Young-Bae Jun relative to Naseem Ajmal India Naseem Ajmal's profile →
Citations per field
00.5×1.5×2.3×
Naseem Ajmal · 1×
Citations per year

Countries citing papers authored by Young-Bae Jun

Since Specialization
Citations

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

Fields of papers citing papers by Young-Bae Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young-Bae Jun. 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 Young-Bae Jun. The network helps show where Young-Bae Jun may publish in the future.

Co-authors

The 25 scholars most cited alongside Young-Bae Jun, 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 Young-Bae Jun Line = papers co-authored together Young-Bae Jun links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Implicative filters of lattice implication algebras
199768
2 200554
3 200842
4 200729
5
PSEUDO-BCI ALGEBRAS
200828
6
Positive implicative and associative filters of lattice implication algebras
199822
7
LI-ideals in lattice implication algebras
199820
8 200916
9 200716
10
Anti Fuzzy Ideals in BCK-algebras
199814
11 201014
12
Rough set theory applied to BCI-algebras
200212
13
FUZZY IDEALS IN NEAR-RINGS
199812
14 200912
15 201011
16 201111
17 201910
18 20068
19 20117
20 20067

About Young-Bae Jun

Young-Bae Jun is a scholar working on Management Science and Operations Research, Computational Theory and Mathematics, Artificial Intelligence, Algebra and Number Theory and Geometry and Topology, having authored 87 papers that have together received 557 indexed citations. Recurring topics across this work include Fuzzy and Soft Set Theory (59 papers), Advanced Algebra and Logic (51 papers), Fuzzy Logic and Control Systems (31 papers), Rough Sets and Fuzzy Logic (18 papers), Multi-Criteria Decision Making (12 papers), Rings, Modules, and Algebras (11 papers), Advanced Topics in Algebra (11 papers) and Matrix Theory and Algorithms (6 papers). The work is most often cited by research in Management Science and Operations Research (432 citations), Computational Theory and Mathematics (415 citations), Algebra and Number Theory (71 citations), Geometry and Topology (61 citations) and Artificial Intelligence (210 citations). Young-Bae Jun has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Mehmet Ali̇ Öztürk, Seok-Zun Song, Chulhwan Park, Sung‐Min Hong, Wiesław A. Dudek, Yang Xu, Keyun Qin, Yang Xu, Hee-Sik Kim and Kavikumar Jacob. Their work appears in journals such as Linear Algebra and its Applications, Journal of the Korean Mathematical Society, Communications of the Korean Mathematical Society, Bulletin of the Korean Mathematical Society and Mathematics.

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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