Graph Labeling and Dimension Problems
Graph Labeling and Dimension Problems is a research topic within Computational Theory and Mathematics. Science Explorer counts 15k research works in it since 1951. 8.7% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on various graph labeling and dimension problems, including metric dimension, resolvability, edge coloring, distinguishing number, irregularity strength, total edge irregularity, neighbor sum distinguishing, antimagic labeling, and computational complexity. The papers explore different aspects of assigning labels to the vertices and edges of graphs with applications in network discovery, security, and cryptographic constructions.
- Graph Labeling
- Metric Dimension
- Resolvability
- Edge Coloring
- Distinguishing Number
- Irregularity Strength
- Total Edge Irregularity
- Neighbor Sum Distinguishing
- Antimagic Labeling
- Computational Complexity
- Research works
- 15k fractional, since 1951
- In the world top 10%
- 1.3k per year above
- Top-10% rate
- 8.7% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +25% the tick is no change
Which countries lead Graph Labeling and Dimension Problems research?
By volume, India and China publish the most (575 and 506 works in 2022–2025).
By volume, 2022–2025
- 1 India 575 works
- 2 China 506 works
- 3 United States 272 works
- 4 Indonesia 257 works
- 5 Brazil 105 works
- 6 Pakistan 80 works
- 7 France 79 works
- 8 Iran 77 works
- 9 United Kingdom 59 works
- 10 Germany 54 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Graph Labeling and Dimension Problems research?
By volume in 2022–2025, Universitas Jember publishes the most Graph Labeling and Dimension Problems research, followed by Universidade Federal de Santa Catarina and Vellore Institute of Technology University.
By volume, 2022–2025
- 1 Universitas JemberIndonesia 49 works
- 2 Universidade Federal de Santa CatarinaBrazil 47 works
- 3 Vellore Institute of Technology UniversityIndia 34 works
- 4 Manonmaniam Sundaranar UniversityIndia 23 works
- 5 Christ UniversityIndia 22 works
- 6 Bandung Institute of TechnologyIndonesia 21 works
- 7 Zhejiang Normal UniversityChina 20 works
- 8 Xinjiang UniversityChina 20 works
- 9 Shri Mata Vaishno Devi UniversityIndia 17 works
- 10 Centre National de la Recherche ScientifiqueFrance 16 works
Who are the leading researchers in Graph Labeling and Dimension Problems?
The most-cited researchers publishing on Graph Labeling and Dimension Problems include Robert E. Tarjan, Bo Liu and Avi Wigderson.
- 1 Robert E. Tarjan United States 3.9k citations
- 2 Bo Liu China 2k citations
- 3 Avi Wigderson United States 1.8k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Graph Labeling and Dimension Problems research done?
The largest centres of Graph Labeling and Dimension Problems research in 2022–2025 are Chennai (India), Jember (Indonesia), Florianópolis (Brazil) and Beijing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Tirunelveli, Xining and Jinhua.
Largest cities, 2022–2025
Where it is the local speciality
- TirunelveliIN · 26.0 works67×
- XiningCN · 23.6 works29×
- JinhuaCN · 20.8 works20×
- FlorianópolisBR · 47.3 works18×
Location quotient: how much more of its research is in Graph Labeling and Dimension Problems than the world average.
Where is the best place to study Graph Labeling and Dimension Problems?
Among universities, judged by research, Riphah International University, Vellore Institute of Technology University and Jazan University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Riphah International UniversityPakistan | 72.3 | 33.9% | 34.5× | 13 | — |
| 2 | Vellore Institute of Technology UniversityIndia | 61.8 | 4.6% | 12.4× | 34 | +347.1% |
| 3 | Jazan UniversitySaudi Arabia | 61.7 | 12.5% | 18.7× | 11 | +207.8% |
| 4 | Universitas JemberIndonesia | 61.1 | 1.0% | 30.4× | 49 | +4065.8% |
| 5 | Menoufia UniversityEgypt | 60.3 | 19.3% | 15.1× | 10 | +148.6% |
| 6 | Christ UniversityIndia | 57.4 | 5.3% | 22.6× | 22 | +534.8% |
| 7 | COMSATS University IslamabadPakistan | 56.2 | 12.6% | 18.6× | 12 | — |
| 8 | Universidade Federal de Santa CatarinaBrazil | 52.9 | 0.0% | 27.2× | 47 | — |
| 9 | Bandung Institute of TechnologyIndonesia | 52.7 | 1.3% | 11.2× | 21 | +266.6% |
| 10 | Central China Normal UniversityChina | 52.4 | 19.7% | 16.2× | 12 | +17.3% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Graph Labeling and Dimension Problems research growing?
Output in 2018–2022 was 25% higher than in 2013–2017, peaking in 2023. The fastest-growing topics are Graph Labeling and Dimension Problems.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.