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Advanced Text Analysis Techniques

Advanced Text Analysis Techniques is a research topic within Artificial Intelligence. Science Explorer counts 35k research works in it since 1950. 21.5% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the automatic extraction of keywords from textual data using various techniques such as graph-based methods, unsupervised approaches, and neural networks. The research explores the application of linguistic knowledge and statistical information to improve the accuracy of keyword extraction from documents.

  • Automatic
  • Extraction
  • Textual Data
  • Keyword
  • Linguistic Knowledge
  • Graph-Based
  • Unsupervised Approach
  • Neural Networks
  • Statistical Information
  • Document
Research works
35k
fractional, since 1950
In the world top 10%
7.5k
per year above
Top-10% rate
21.5%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+35%
the tick is no change

Which countries lead Advanced Text Analysis Techniques research?

By volume, China and India publish the most (2.4k and 1.4k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 2.4k works
  2. 2 India 1.4k works
  3. 3 United States 809 works
  4. 4 Indonesia 292 works
  5. 5 Japan 259 works
  6. 6 Germany 211 works
  7. 7 United Kingdom 180 works
  8. 8 Russia 158 works
  9. 9 Türkiye 142 works
  10. 10 South Korea 141 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: 39.6%India: 23.6%United States: 13.6%Indonesia: 4.9%6 others listed: 18.3%40%largest
China2,362 · 39.6%India1,405 · 23.6%United States809 · 13.6%Indonesia292 · 4.9%6 others listed1,091 · 18.3%

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

Which institutions lead Advanced Text Analysis Techniques research?

By volume in 2022–2025, Beijing University of Posts and Telecommunications publishes the most Advanced Text Analysis Techniques research, followed by Vellore Institute of Technology University and SRM Institute of Science and Technology.

Who are the leading researchers in Advanced Text Analysis Techniques?

The most-cited researchers publishing on Advanced Text Analysis Techniques include Marko Sarstedt, Philip S. Yu and Witold Pedrycz.

  1. 1 Marko Sarstedt Germany 11k citations
  2. 2 Philip S. Yu United States 6.6k citations
  3. 3 Witold Pedrycz Canada 5.4k citations
  4. 4 Jiawei Han United States 5.2k citations

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

Where is Advanced Text Analysis Techniques research done?

The largest centres of Advanced Text Analysis Techniques research in 2022–2025 are Beijing (China), Shanghai (China), Wuhan (China) and Chennai (India). Among places with at least 20 works in it, it is an unusually large share of all research in Vijayawada.

Largest cities, 2022–2025

  1. 1 Beijing China 488 works
  2. 2 Shanghai China 143 works
  3. 3 Wuhan China 130 works
  4. 4 Chennai India 127 works
  5. 5 Nanjing China 117 works
  6. 6 Guangzhou China 109 works
  7. 7 Tokyo Japan 108 works
  8. 8 Bengaluru India 97 works
  9. 9 Chengdu China 95 works
  10. 10 New Delhi India 81 works

Where it is the local speciality

  1. VijayawadaIN · 25.5 works6.7×
← less than its size predictsmore →

Location quotient: how much more of its research is in Advanced Text Analysis Techniques than the world average.

See Advanced Text Analysis Techniques on the map

Where is the best place to study Advanced Text Analysis Techniques?

Among universities, judged by research, Amrita Vishwa Vidyapeetham, Delhi Technological University and Nanyang Technological 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 23.43%fractional works in this node (log) →share in the world top 10% →Amrita Vishwa Vidyapeetham: 36, 25.8%Delhi Technological University: 27, 17.1%Nanyang Technological University: 21, 37.7%Nanjing University of Science and Technology: 23, 32.9%Binus University: 30, 13.7%University of Hassan II Casablanca: 13, 37.6%Xinjiang University: 25, 25.2%Vellore Institute of Technology University: 39, 11.8%King Abdulaziz University: 15, 24.2%Communication University of China: 13, 8.3%Nanyang Technologica…Nanjing University o…Amrita Vishwa Vidyap…Delhi Technological …
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Amrita Vishwa VidyapeethamIndia 73.925.8%8.1×36 +661.1%
2 Delhi Technological UniversityIndia 67.617.1%12.0×27 +255.2%
3 Nanyang Technological UniversitySingapore 61.337.7%3.2×21 +44.5%
4 Nanjing University of Science and TechnologyChina 61.232.9%3.4×23 +258.3%
5 Binus UniversityIndonesia 57.713.7%6.7×30 +879.5%
6 University of Hassan II CasablancaMorocco 56.737.6%6.1×13
7 Xinjiang UniversityChina 56.325.2%7.1×25
8 Vellore Institute of Technology UniversityIndia 55.411.8%4.8×39 +1480.4%
9 King Abdulaziz UniversitySaudi Arabia 55.324.2%3.4×15 +550.9%
10 Communication University of ChinaChina 53.08.3%15.5×13 +314.5%

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 Advanced Text Analysis Techniques research growing?

Output in 2018–2022 was 35% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Advanced Text Analysis Techniques.

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.