Peter A. Ng

72 papers receiving 433 citations

Peers

Peter A. Ng
Comparison fields: 5 of 63
  • Artificial Intelligence 301
  • Computer Networks and Communications 201
  • Signal Processing 91
  • Information Systems 168
  • Software 25
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Ruy Luiz Milidiú Brazil
Alva Couch United States
Μαρία Θεοδωρίδου Greece
Devesh Kumar Srivastava India
G. Coulson United Kingdom
Line Pouchard United States
Manolis Gergatsoulis Greece
A. Vinaya Babu India
Erkang Zhu Canada
Wenpin Jiao China
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Citations per year

Countries citing papers authored by Peter A. Ng

Since Specialization
Citations

This map shows the geographic impact of Peter A. Ng'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 Peter A. Ng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter A. Ng more than expected).

Fields of papers citing papers by Peter A. Ng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter A. Ng. 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 Peter A. Ng. The network helps show where Peter A. Ng may publish in the future.

Co-authors

The 25 scholars most cited alongside Peter A. Ng, 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 Peter A. Ng Line = papers co-authored together Peter A. Ng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1 198340
2 200530
3 199229
4
Modern Software Engineering: Foundations and Current Perspectives
198927
5 199624
6 201419
7 199118
8 198117
9 200316
10 201715
11 199913
12 199611
13 199410
14 199410
15 198410
16
An Intelligent Documentation Support Environment.
19939
17 19969
18 19959
19 19979
20 19968

About Peter A. Ng

Peter A. Ng is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Signal Processing, having authored 85 papers that have together received 492 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (28 papers), Advanced Database Systems and Queries (28 papers), Data Management and Algorithms (14 papers), Handwritten Text Recognition Techniques (9 papers), Service-Oriented Architecture and Web Services (8 papers), Image Retrieval and Classification Techniques (8 papers), Business Process Modeling and Analysis (6 papers) and Rough Sets and Fuzzy Logic (6 papers). The work is most often cited by research in Artificial Intelligence (301 citations), Computer Networks and Communications (201 citations), Signal Processing (91 citations), Information Systems (168 citations) and Software (25 citations). Peter A. Ng has collaborated with scholars based in United States, Singapore and Taiwan. Frequent co-authors include Jason T. L. Wang, Sushil Jajodia, Raymond T. Yeh, Jeanne M. Jones, Nathan Wood, Sam Yuan Sung, Wilhelm Rossak, Gang Zhou, Xuhong Li and Yao Liu. Their work appears in journals such as Information Sciences, IEEE Transactions on Software Engineering, Techniques and methods, IEEE Transactions on Knowledge and Data Engineering and Data & Knowledge Engineering.

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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