John E. Galletly

515 citations
19 papers · 381 · h-index 6

Impact in

Papers in

John E. Galletly

16 papers receiving 333 citations

Peers

John E. Galletly
Comparison fields: 5 of 92
  • Industrial and Manufacturing Engineering 66
  • Management Information Systems 35
  • Artificial Intelligence 118
  • Software 14
  • Management Science and Operations Research 39
Replace Douglas J. White with:
Douglas J. White United Kingdom
Noureddine Bouhmala Norway
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Citations per field
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Citations per year

Countries citing papers authored by John E. Galletly

Since Specialization
Citations

This map shows the geographic impact of John E. Galletly's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John E. Galletly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John E. Galletly more than expected).

Fields of papers citing papers by John E. Galletly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John E. Galletly. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John E. Galletly. The network helps show where John E. Galletly may publish in the future.

Co-authors

The 3 scholars most cited alongside John E. Galletly, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John E. Galletly Line = papers co-authored together John E. Galletly links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 1992289
2 199421
3 199315
4 199412
5 199410
6 200310
7
Native browser support for 3D rendering and physics using WebGL, HTML5 and Javascript.
20136
8 19913
9 20033
10 19923
11 19902
12
Towards an intelligent syntax checker
19892
13 19911
14 19921
15 19891
16 19941
17 19981
18 19850
19 20030

About John E. Galletly

John E. Galletly is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering, Management Science and Operations Research, Hardware and Architecture and Management Information Systems, having authored 19 papers that have together received 381 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (3 papers), Fuzzy Logic and Control Systems (3 papers), Distributed and Parallel Computing Systems (3 papers), Real-Time Systems Scheduling (2 papers), Speech and dialogue systems (2 papers), Embedded Systems Design Techniques (2 papers), Intelligent Tutoring Systems and Adaptive Learning (2 papers) and Scheduling and Optimization Algorithms (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (66 citations), Management Information Systems (35 citations), Artificial Intelligence (118 citations), Software (14 citations) and Management Science and Operations Research (39 citations). John E. Galletly has collaborated with scholars based in United Kingdom, Bulgaria and Poland. Frequent co-authors include John Bicheno, Vladimir Kolovski and Andrew Hoi‐Tao Wong. Their work appears in journals such as Industrial Management & Data Systems, Journal of Computer Assisted Learning, International Journal of Operations & Production Management, Computer Assisted Language Learning and Journal of Magnetism and Magnetic Materials.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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