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Topic · Signal Processing

Data Management and Algorithms

Data Management and Algorithms is a research topic within Signal Processing. Science Explorer counts 55k research works in it since 1950. 10.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the mining, analysis, and querying of GPS trajectories and moving object data. It covers topics such as trajectory clustering, skyline computation, similarity search, top-k query processing, probabilistic databases, location prediction, and semantic trajectory modeling.

  • Trajectory Data Mining
  • GPS Trajectories
  • Skyline Operator
  • Similarity Search
  • Spatial Databases
  • Top-k Query Processing
  • Probabilistic Databases
  • Location Prediction
  • Clustering Algorithms
  • Semantic Trajectories
Research works
55k
fractional, since 1950
In the world top 10%
5.5k
per year above
Top-10% rate
10.0%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
-19%
the tick is no change
Largest producer
China
42% of the 10 largest, 2022-now
Data Management and Algorithms

Which countries lead Data Management and Algorithms research?

By volume, China and the United States publish the most (1.7k and 771 works in 2022-now).

By volume, 2022-now

  1. 1 China 1.7k works
  2. 2 United States 771 works
  3. 3 India 376 works
  4. 4 Germany 265 works
  5. 5 France 225 works
  6. 6 Japan 165 works
  7. 7 Italy 159 works
  8. 8 United Kingdom 143 works
  9. 9 Canada 127 works
  10. 10 Australia 106 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.

China: 42.4%United States: 19.0%India: 9.3%Germany: 6.5%6 others listed: 22.8%42%largest
China1,716 · 42.4%United States771 · 19.0%India376 · 9.3%Germany265 · 6.5%6 others listed924 · 22.8%

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

Which institutions lead Data Management and Algorithms research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Data Management and Algorithms research, followed by Chinese Academy of Sciences and Tsinghua University.

By volume, 2022-now

  1. 1 Centre National de la Recherche ScientifiqueFrance 77 works
  2. 2 Chinese Academy of SciencesChina 61 works
  3. 3 Tsinghua UniversityChina 36 works
  4. 4 Wuhan UniversityChina 34 works
  5. 5 Zhejiang UniversityChina 26 works
  6. 6 National University of Defense TechnologyChina 26 works
  7. 7 Harbin Institute of TechnologyChina 25 works
  8. 8 Shanghai Jiao Tong UniversityChina 24 works
  9. 9 University of Electronic Science and Technology of ChinaChina 24 works
  10. 10 Beihang UniversityChina 23 works

Who are the leading researchers in Data Management and Algorithms?

The most-cited researchers publishing on Data Management and Algorithms include Yoshua Bengio, Robert John Tibshirani and Amos Tversky.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Robert John Tibshirani United States 396k citations
  3. 3 Amos Tversky United States 327k citations
  4. 4 Xiaogang Wang China 260k citations
  5. 5 Andrew Zisserman United Kingdom 255k citations
  6. 6 Leo Breiman United States 243k citations
  7. 7 Li Fei-Fei United States 225k citations
  8. 8 Jerome H. Friedman United States 224k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Data Management and Algorithms?

The most cited paper in Data Management and Algorithms is "Silhouettes: A graphical aid to the interpretation and validation of cluster analysis" (Peter J. Rousseeuw, 1987), with 21,780 citations. Next come "A density-based algorithm for discovering clusters in large spatial Databases with Noise" (19,125) and "The WEKA data mining software" (17,902).

Most cited papers
#PaperReleasedCitations
1 Silhouettes: A graphical aid to the interpretation and validation of cluster analysis Peter J. Rousseeuw · Journal of Computational and Applied Mathematics Open access Nov 1987 21,780
2 A density-based algorithm for discovering clusters in large spatial Databases with Noise Martin Ester, Hans‐Peter Kriegel, Jörg Sander et al. 1996 19,125
3 The WEKA data mining software Mark Michael Hall, Eibe Frank, Geoffrey Holmes et al. · ACM SIGKDD Explorations Newsletter Open access 16 Nov 2009 17,902
4 Data clustering Anil Kumar Jain, Musti Narasimha Murty, Patrick J. Flynn · ACM Computing Surveys Open access Sep 1999 13,296
5 A Formal Basis for the Heuristic Determination of Minimum Cost Paths Peter Hart, Nils J. Nilsson, Bertram Raphael · IEEE Transactions on Systems Science and Cybernetics 1968 12,723
All 99 most cited papers, with filters and sorting

Where is Data Management and Algorithms research done?

The largest centres of Data Management and Algorithms research in 2022-now are Beijing (China), Shanghai (China), Wuhan (China) and Nanjing (China).

Largest cities, 2022-now

  1. 1 BeijingChina 338 works
  2. 2 ShanghaiChina 113 works
  3. 3 WuhanChina 98 works
  4. 4 NanjingChina 85 works
  5. 5 Hong KongChina 71 works
  6. 6 Xi'anChina 69 works
  7. 7 HangzhouChina 69 works
  8. 8 ChengduChina 65 works
  9. 9 ParisFrance 65 works
  10. 10 ChangshaChina 60 works
See Data Management and Algorithms on the map

Where is the best place to study Data Management and Algorithms?

Among universities, judged by research, Hong Kong University of Science and Technology, Nanyang Technological University and Tsinghua 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.

0%20%40%mean 27.86%fractional works in this field (log) →share of work in the world top 10% →Nanyang Technologica…Tsinghua UniversityHong Kong University…Chinese University o…
above the meannear itbelow it

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.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Hong Kong University of Science and TechnologyChina 85.725.7%10.6×21 +33.7%
2Nanyang Technological UniversitySingapore 78.335.0%5.0×19 +3.8%
3Tsinghua UniversityChina 73.528.9%3.2×36 -7.5%
4Chinese University of Hong KongChina 72.422.7%5.3×19 +8.2%
5University of Hong KongChina 68.530.5%2.4×11 +24.9%
6City University of Hong KongChina 65.237.7%3.5×10 +11.2%
7Beihang UniversityChina 63.221.9%4.2×23 +66.1%
8University of Electronic Science and Technology of ChinaChina 61.626.4%4.3×24 -17.6%
9Zhejiang UniversityChina 61.022.0%2.0×26 +3.6%
10Aalborg UniversityDenmark 60.527.8%5.1×14 -51.4%

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 Data Management and Algorithms, country by country

Is Data Management and Algorithms research growing?

Output in 2022-2025 was 19% lower than in 2018-2021, peaking in 2009.

still counting19801990200020102020
grewheldshrank

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 Data Management and Algorithms as a percentage of every work published that year, 0.027% in 2024.

still counting0.050%0.10%0.15%Data Management and Algorithms0.025% in 202519801990200020102020

Fractional works of Data Management and Algorithms 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.

still counting5%10%15%Data Management and Algorithms9.9% in 2025200020102020

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.

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