Ken Kahn

2.4k citations
82 papers · 1.3k · h-index 17

Impact in

Papers in

Ken Kahn

77 papers receiving 1.1k citations

Peers

Ken Kahn
Comparison fields: 5 of 107
  • Computer Science Applications 328
  • Software 144
  • Hardware and Architecture 156
  • Artificial Intelligence 619
  • Human-Computer Interaction 102
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Citations per field
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Citations per year

Countries citing papers authored by Ken Kahn

Since Specialization
Citations

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

Fields of papers citing papers by Ken Kahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ken Kahn. 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 Ken Kahn. The network helps show where Ken Kahn may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1986141
2 1977121
3 1996107
4 198696
5 198692
6 202156
7 200249
8 198740
9 202039
10
Janus: a step towards distributed constraint programming
199039
11 201131
12 199631
13 198627
14 201227
15 199021
16
The Compilation of Prolog Programs without the Use of a Prolog Compiler.
198417
17
A Computer Game To Teach Programming.
199917
18 198616
19
UNIFORM - A Language Based Upon Unification Which Unifies (much of) LISP, PROLOG, and ACT 1.
198115
20
How to Implement Prolog on a LISP Machine.
198414

About Ken Kahn

Ken Kahn is a scholar working on Artificial Intelligence, Computer Science Applications, Computer Networks and Communications, Software and Information Systems, having authored 82 papers that have together received 1.3k indexed citations. Recurring topics across this work include Teaching and Learning Programming (19 papers), Logic, programming, and type systems (10 papers), Logic, Reasoning, and Knowledge (10 papers), AI-based Problem Solving and Planning (7 papers), Constraint Satisfaction and Optimization (5 papers), Human Motion and Animation (4 papers), Semantic Web and Ontologies (4 papers) and Model-Driven Software Engineering Techniques (4 papers). The work is most often cited by research in Computer Science Applications (328 citations), Software (144 citations), Hardware and Architecture (156 citations), Artificial Intelligence (619 citations) and Human-Computer Interaction (102 citations). Ken Kahn has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include Daniel G. Bobrow, Mark Stefik, G. Anthony Gorry, Vijay Saraswat, Niall Winters, Frank Zdybel, Larry Masinter, Gregor Kiczales, Mats Carlsson and Mark S. Miller. Their work appears in journals such as ACM SIGPLAN Notices, Communications of the ACM, Journal of Visual Languages & Computing, Future Generation Computer Systems and AI Magazine.

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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