John Lamping

5.7k citations
31 papers · 1.6k · 1 hit paper · h-index 16

Impact in

Papers in

John Lamping

31 papers receiving 1.4k citations

John Lamping's Hit Papers

A focus+context technique based on hyperbolic geometry for visualizing large hierarchies 1995 · 533 citations
5330+10+20Years since publication100200300400500

Peers

John Lamping
Comparison fields: 5 of 70
  • Human-Computer Interaction 216
  • Computer Vision and Pattern Recognition 622
  • Information Systems and Management 164
  • Artificial Intelligence 664
  • Software 77
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Citations per year

Countries citing papers authored by John Lamping

Since Specialization
Citations

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

Fields of papers citing papers by John Lamping

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A focus+context technique based on hyperbolic geometry for visualizing large hierarchies
Hit paper breakdown →
1995533
2 2000143
3 2001131
4 1994130
5 1990118
6 1995109
7 199772
8 199347
9 199642
10 199240
11 199335
12 199933
13
RG: A Case-Study for Aspectoriented Programming
199725
14 199722
15 198222
16 200015
17
The Role of the Base in Aspect Oriented Programming
199914
18 198813
19 200213
20 199112

About John Lamping

John Lamping is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Hardware and Architecture, having authored 31 papers that have together received 1.6k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Distributed systems and fault tolerance (6 papers), Logic, programming, and type systems (6 papers), Logic, Reasoning, and Knowledge (6 papers), Parallel Computing and Optimization Techniques (4 papers), Data Visualization and Analytics (3 papers), Software System Performance and Reliability (2 papers) and Service-Oriented Architecture and Web Services (2 papers). The work is most often cited by research in Human-Computer Interaction (216 citations), Computer Vision and Pattern Recognition (622 citations), Information Systems and Management (164 citations), Artificial Intelligence (664 citations) and Software (77 citations). John Lamping has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Ramana Rao, Peter Pirolli, Gregor Kiczales, Mark Yim, Ying Zhang, Paul Dourish, David A. Nichols, Michael Dixon, Pavel Curtis and Karin Anna Petersen. Their work appears in journals such as ACM SIGPLAN Notices, Journal of Logic Language and Information, ACM Transactions on Information Systems, Autonomous Robots and Behavioral and Brain Sciences.

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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