Jeff Naughton

1.4k citations
17 papers · 683 indexed · h-index 13

Impact in

Papers in

Jeff Naughton

17 papers receiving 607 citations

Peers

Jeff Naughton
Comparison fields: 5 of 38
  • Signal Processing 185
  • Computer Networks and Communications 387
  • Management Science and Operations Research 202
  • Artificial Intelligence 432
  • Information Systems 187
Replace Reinhard Pichler with:
Reinhard Pichler Austria
Immanuel Trummer United States
Fereidoon Sadri United States
David Toman Canada
Balder ten Cate United States
Ahmed Metwally United States
José A. Blakeley United States
Jeff Ullman United States
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Andrey Gubichev Germany
Jeff Naughton relative to Reinhard Pichler Austria Reinhard Pichler's profile →
Citations per field
00.5×1.5×2.5×
Reinhard Pichler · 1×
Citations per year

Countries citing papers authored by Jeff Naughton

Since Specialization
Citations

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

Fields of papers citing papers by Jeff Naughton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 20222
2 20214
3 202021
4 202012
5 202011
6 20184
7 201812
8 201612
9 2016153
10 201641
11 200643
12 1998138
13
Estimating the size of generalized transitive closures
198945
14 198950
15 198741
16 198748
17 198546

About Jeff Naughton

Jeff Naughton is a scholar working on Computer Networks and Communications, Management Science and Operations Research, Signal Processing, Information Systems and Software, having authored 17 papers that have together received 683 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (15 papers), Data Quality and Management (8 papers), Web Data Mining and Analysis (4 papers), Data Management and Algorithms (4 papers), Logic, Reasoning, and Knowledge (3 papers), Cloud Computing and Resource Management (3 papers), Semantic Web and Ontologies (2 papers) and Distributed systems and fault tolerance (2 papers). The work is most often cited by research in Signal Processing (185 citations), Computer Networks and Communications (387 citations), Management Science and Operations Research (202 citations), Artificial Intelligence (432 citations) and Information Systems (187 citations). Jeff Naughton has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Yehoshua Sagiv, R.J. Lipton, Cristian Estan, Han Li, Adel Ardalan, Pradap Konda, Haojun Zhang, Sanjib Das, Shishir Prasad and AnHai Doan. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM SIGMOD Record, Communications of the ACM, The VLDB Journal and Very Large Data Bases.

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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