Jeff Naughton
Impact in
- Signal Processing top 5%
- Data Management and Algorithms
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- Advanced Database Systems and Queries
- Distributed systems and fault tolerance
Papers in
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- Advanced Database Systems and Queries 15
- Distributed systems and fault tolerance 2
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- Data Quality and Management 8
- Co-authors
- Yehoshua SagivR.J. LiptonCristian EstanHan LiAdel ArdalanPradap KondaHaojun ZhangSanjib Das
- Journals
- Proceedings of the VLDB Endowment (5 papers)ACM SIGMOD Record (4 papers)Communications of the ACM (1 paper)The VLDB Journal (1 paper)Very Large Data Bases (1 paper)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Jeff Naughton
17 papers receiving 607 citations
Peers
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
Countries citing papers authored by Jeff Naughton
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
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 2 | |
| 2 | 2021 | 4 | |
| 3 | 2020 | 21 | |
| 4 | 2020 | 12 | |
| 5 | 2020 | 11 | |
| 6 | 2018 | 4 | |
| 7 | 2018 | 12 | |
| 8 | 2016 | 12 | |
| 9 | 2016 | 153 | |
| 10 | 2016 | 41 | |
| 11 | 2006 | 43 | |
| 12 | 1998 | 138 | |
| 13 | Estimating the size of generalized transitive closures | 1989 | 45 |
| 14 | 1989 | 50 | |
| 15 | 1987 | 41 | |
| 16 | 1987 | 48 | |
| 17 | 1985 | 46 |
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.