Cognitive Computing and Networks
Cognitive Computing and Networks is a research topic within Artificial Intelligence. Science Explorer counts 7.8k research works in it since 1957. 10.0% of them reached the world's top 10% most cited for their field and year.
This cluster of papers explores the theoretical framework of cognitive informatics, computational intelligence, and related fields. It covers topics such as semantic link networks, neural informatics, denotational mathematics, brain-inspired systems, cognitive computing, semantic analysis, knowledge representation, and the impact on the cyber-physical society.
- Cognitive Informatics
- Semantic Link Network
- Computational Intelligence
- Neural Informatics
- Denotational Mathematics
- Brain-Inspired Systems
- Cognitive Computing
- Semantic Analysis
- Knowledge Representation
- Cyber-Physical Society
- Research works
- 7.8k fractional, since 1957
- In the world top 10%
- 785 per year above
- Top-10% rate
- 10.0% share of its works in the world top 10%
- Growth, 2018-21 → 2022-25
- +52% the tick is no change
- Largest producer
China
48% of the 10 largest, 2022-now
Which countries lead Cognitive Computing and Networks research?
By volume, China and the United States publish the most (626 and 206 works in 2022-now).
By volume, 2022-now
- 1
China 626 works
- 2
United States 206 works
- 3
India 173 works
- 4
Russia 75 works
- 5
United Kingdom 47 works
- 6
Germany 46 works
- 7
Japan 37 works
- 8
Poland 32 works
- 9
France 32 works
- 10
Ukraine 28 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 Cognitive Computing and Networks research?
By volume in 2022-now, Beijing University of Posts and Telecommunications publishes the most Cognitive Computing and Networks research, followed by Chinese Academy of Sciences and Russian Academy of Sciences.
By volume, 2022-now
- 1
Beijing University of Posts and Telecommunications
China 24 works
- 2
Chinese Academy of Sciences
China 15 works
- 3
Russian Academy of Sciences
Russia 13 works
- 4
Tsinghua University
China 11 works
- 5
Centre National de la Recherche Scientifique
France 11 works
- 6
National University of Defense Technology
China 11 works
- 7
National University of Singapore
Singapore 11 works
- 8
Zhejiang University
China 9 works
- 9
National Research Nuclear University MEPhI
Russia 8 works
- 10
Shanghai Jiao Tong University
China 8 works
Who are the leading researchers in Cognitive Computing and Networks?
The most-cited researchers publishing on Cognitive Computing and Networks include Herbert A. Simon and H. Vincent Poor.
- 1
Herbert A. Simon
United States 179k citations
- 2
H. Vincent Poor
United States 165k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Cognitive Computing and Networks research done?
The largest centres of Cognitive Computing and Networks research in 2022-now are Beijing (China), Moscow (Russia), Shanghai (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Chennai, Beijing and Xi'an.
Largest cities, 2022-now
Where it is the local speciality
- ChennaiIN · 22.7 works2.7×
- BeijingCN · 153.9 works2.7×
- Xi'anCN · 34.2 works2.6×
Location quotient: how much more of its research is in Cognitive Computing and Networks than the world average.
Where is the best place to study Cognitive Computing and Networks?
Among universities, judged by research, Beijing University of Posts and Telecommunications, Tsinghua University and Zhejiang 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 first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Beijing University of Posts and Telecommunications |
91.3 | 26.7% | 25.3× | 24 | +1144.5% |
| 2 | Tsinghua University |
62.8 | 24.7% | 3.3× | 11 | +491.1% |
| 3 | Zhejiang University |
41.6 | 18.6% | 2.2× | 9 | +425.7% |
| 4 | National University of Defense Technology |
36.4 | 12.4% | 9.2× | 11 | +32.6% |
| 5 | Shanghai Jiao Tong University |
31.5 | 15.2% | 1.9× | 8 | +114.4% |
| 6 | National University of Singapore |
30.8 | 3.4% | 5.9× | 10 | - |
| 7 | National Research Nuclear University MEPhI |
12.5 | 1.9% | 44.0× | 8 | -24.3% |
Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.
Every institution in Cognitive Computing and Networks, country by countryIs Cognitive Computing and Networks research growing?
Output in 2022-2025 was 52% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Cognitive Computing and Networks.
The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.
Its share of all research
Growing output can still be a shrinking share: all of science grows. This is Cognitive Computing and Networks as a percentage of every work published that year, 0.0087% in 2024.
Fractional works of Cognitive Computing and Networks over all fractional works that year. How the balance of science has shifted.
How much of it reaches the world top 10%
Year by year.
Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.
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.
Discussion
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