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Topic · Artificial Intelligence

Experience-Based Knowledge Management

Experience-Based Knowledge Management is a research topic within Artificial Intelligence. Science Explorer counts 600 research works in it since 1953. 7.8% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on experience-based knowledge representation and management, including the development of Decisional DNA and Set of Experience Knowledge Structure within ontology systems. It also explores the application of these structures in renewable energy sources, international standards, Internet of Things, cognitive vision systems, and environmental management.

  • Decisional DNA
  • Set of Experience Knowledge Structure
  • Ontology System
  • Renewable Energy Sources
  • International Standards
  • Internet of Things
  • Cognitive Vision Systems
  • Information Technology
  • Semantic-based Academic Social Network
  • Environmental Management
Research works
600
fractional, since 1953
In the world top 10%
47
per year above
Top-10% rate
7.8%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-23%
the tick is no change

Which countries lead Experience-Based Knowledge Management research?

By volume, the United States and Indonesia publish the most (24 and 13 works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 24 works
  2. 2 Indonesia 13 works
  3. 3 China 6 works
  4. 4 Spain 4 works
  5. 5 Poland 3 works
  6. 6 India 3 works
  7. 7 Taiwan 2 works
  8. 8 Germany 2 works
  9. 9 Italy 2 works
  10. 10 France 2 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.

United States: 39.0%Indonesia: 21.8%China: 9.2%Spain: 5.9%6 others listed: 24.1%39%largest
United States24 · 39.0%Indonesia13 · 21.8%China6 · 9.2%Spain4 · 5.9%6 others listed15 · 24.1%

Shares of the rows listed above, not of the whole node.

Which institutions lead Experience-Based Knowledge Management research?

By volume in 2022–2025, Missouri University of Science and Technology publishes the most Experience-Based Knowledge Management research, followed by National Taipei University of Technology and LI-COR Biosciences (United States).

By volume, 2022–2025

  1. 1 Missouri University of Science and Technology United States 2 works
  2. 2 National Taipei University of Technology Taiwan 1 works
  3. 3 LI-COR Biosciences (United States) United States 1 works
  4. 4 Gdańsk University of Technology Poland 1 works
  5. 5 Politecnico di Milano Italy 1 works
  6. 6 Delft University of Technology Netherlands 1 works
  7. 7 University of Florida United States 1 works
  8. 8 National Chin-Yi University of Technology Taiwan 1 works
  9. 9 Cefriel Italy 1 works
  10. 10 University of Novi Sad Serbia 1 works

Where is Experience-Based Knowledge Management research done?

The largest centres of Experience-Based Knowledge Management research in 2022–2025 are Rolla (United States), Beijing (China), Jakarta (Indonesia) and Surabaya (Indonesia). Among places with at least 20 works in it, it is an unusually large share of all research in Gdańsk.

Largest cities, 2022–2025

  1. 1 Rolla United States 2 works
  2. 2 Beijing China 2 works
  3. 3 Jakarta Indonesia 2 works
  4. 4 Surabaya Indonesia 2 works
  5. 5 Milan Italy 2 works
  6. 6 St Louis United States 1 works
  7. 7 Madrid Spain 1 works
  8. 8 Shanghai China 1 works
  9. 9 Barcelona Spain 1 works
  10. 10 Taipei Taiwan 1 works

Where it is the local speciality

  1. GdańskPL · 20.7 works58×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Experience-Based Knowledge Management than the world average.

See Experience-Based Knowledge Management on the map

Is Experience-Based Knowledge Management research growing?

Output in 2018–2022 was 23% lower than in 2013–2017, peaking in 2025. The fastest-growing topics are Experience-Based Knowledge Management.

19801990200020102020
grewheldshrank

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.