H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 81 Citations 23,865 201 World Ranking 408 National Ranking 245

Research.com Recognitions

Awards & Achievements

2008 - ACM Software System Award For Gamma, the first embodiment of a parallel, "shared nothing" database system running on a cluster of commodity computers, using data partitioning and innovative parallel query execution strategies.

2002 - ACM Fellow For contributions to database system research and practice.

Overview

What is he best known for?

The fields of study he is best known for:

  • Database
  • Operating system
  • Programming language

His main research concerns Theoretical computer science, Database, XML, Data mining and Query optimization. His research in Theoretical computer science intersects with topics in Tree, Multidimensional analysis, Set and Online analytical processing. His Database research includes themes of Object, Smart Cache and Cache.

The various areas that Jeffrey F. Naughton examines in his XML study include Inverted index and Relational database, Relational database management system. His Data mining study integrates concerns from other disciplines, such as Host and Data set. His Query optimization research also works with subjects such as

  • Conjunctive query and Query by Example most often made with reference to Sargable,
  • Query language which connect with Tuple.

His most cited work include:

  • Relational Databases for Querying XML Documents: Limitations and Opportunities (974 citations)
  • On supporting containment queries in relational database management systems (782 citations)
  • On the Computation of Multidimensional Aggregates (498 citations)

What are the main themes of his work throughout his whole career to date?

Data mining, Database, Theoretical computer science, Query optimization and Information retrieval are his primary areas of study. The concepts of his Database study are interwoven with issues in Web search query and Cache. His Theoretical computer science research is multidisciplinary, incorporating perspectives in Algorithm, Online analytical processing, Joins and Join.

His Query optimization research is multidisciplinary, incorporating elements of Query language, Query expansion, XML, Sargable and View. His Information retrieval research integrates issues from XML validation, Efficient XML Interchange and XML database. His Relational database research incorporates themes from SQL and Tuple.

He most often published in these fields:

  • Data mining (20.95%)
  • Database (20.16%)
  • Theoretical computer science (19.37%)

What were the highlights of his more recent work (between 2013-2021)?

  • Data mining (20.95%)
  • Theoretical computer science (19.37%)
  • Distributed computing (10.28%)

In recent papers he was focusing on the following fields of study:

Jeffrey F. Naughton mainly investigates Data mining, Theoretical computer science, Distributed computing, Query optimization and Data management. The Data mining study combines topics in areas such as Workload, Key and Greedy algorithm. Programming language is closely connected to Algebraic number in his research, which is encompassed under the umbrella topic of Theoretical computer science.

Jeffrey F. Naughton interconnects Cardinality and Sargable in the investigation of issues within Query optimization. His Sargable research incorporates elements of Query expansion and Database. His Database research includes themes of Inverted index, Semantics and Search-oriented architecture.

Between 2013 and 2021, his most popular works were:

  • Corleone: hands-off crowdsourcing for entity matching (146 citations)
  • Magellan: toward building entity matching management systems (117 citations)
  • Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics (103 citations)

In his most recent research, the most cited papers focused on:

  • Database
  • Operating system
  • Programming language

His primary areas of study are Data mining, Data management, World Wide Web, Big data and Distributed computing. Jeffrey F. Naughton focuses mostly in the field of Data mining, narrowing it down to matters related to Sargable and, in some cases, Theoretical computer science. In his research on the topic of Data management, Feature selection, Decision rule, Semi-supervised learning and Machine learning is strongly related with Normalization.

His World Wide Web research incorporates themes from Python, Visualization, Data science and Scripting language. His Distributed computing study combines topics in areas such as Data processing system, Unavailability, Semantics and Differential privacy. The study incorporates disciplines such as Tuple, Set and Database in addition to Cloud computing.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Relational Databases for Querying XML Documents: Limitations and Opportunities

Jayavel Shanmugasundaram;Kristin Tufte;Chun Zhang;Gang He.
very large data bases (1999)

1757 Citations

On supporting containment queries in relational database management systems

Chun Zhang;Jeffrey Naughton;David DeWitt;Qiong Luo.
international conference on management of data (2001)

1303 Citations

On the Computation of Multidimensional Aggregates

Sameet Agarwal;Rakesh Agrawal;Prasad Deshpande;Ashish Gupta.
very large data bases (1996)

922 Citations

The 007 Benchmark

Michael J. Carey;David J. DeWitt;Jeffrey F. Naughton.
international conference on management of data (1993)

737 Citations

Shoring up persistent applications

Michael J. Carey;David J. DeWitt;Michael J. Franklin;Nancy E. Hall.
international conference on management of data (1994)

677 Citations

Generalized Search Trees for Database Systems

Joseph M. Hellerstein;Jeffrey F. Naughton;Avi Pfeffer.
very large data bases (1995)

674 Citations

An array-based algorithm for simultaneous multidimensional aggregates

Yihong Zhao;Prasad M. Deshpande;Jeffrey F. Naughton.
international conference on management of data (1997)

637 Citations

Evaluating window joins over unbounded streams

J. Kang;J.F. Naughton;S.D. Viglas.
international conference on data engineering (2003)

533 Citations

Covering indexes for branching path queries

Raghav Kaushik;Philip Bohannon;Jeffrey F Naughton;Henry F Korth.
international conference on management of data (2002)

472 Citations

Materialized View Selection for Multidimensional Datasets

Amit Shukla;Prasad Deshpande;Jeffrey F. Naughton.
very large data bases (1998)

411 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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