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.
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
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.
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.
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.
Relational Databases for Querying XML Documents: Limitations and Opportunities
Jayavel Shanmugasundaram;Kristin Tufte;Chun Zhang;Gang He.
very large data bases (1999)
On supporting containment queries in relational database management systems
Chun Zhang;Jeffrey Naughton;David DeWitt;Qiong Luo.
international conference on management of data (2001)
On the Computation of Multidimensional Aggregates
Sameet Agarwal;Rakesh Agrawal;Prasad Deshpande;Ashish Gupta.
very large data bases (1996)
The 007 Benchmark
Michael J. Carey;David J. DeWitt;Jeffrey F. Naughton.
international conference on management of data (1993)
Shoring up persistent applications
Michael J. Carey;David J. DeWitt;Michael J. Franklin;Nancy E. Hall.
international conference on management of data (1994)
Generalized Search Trees for Database Systems
Joseph M. Hellerstein;Jeffrey F. Naughton;Avi Pfeffer.
very large data bases (1995)
An array-based algorithm for simultaneous multidimensional aggregates
Yihong Zhao;Prasad M. Deshpande;Jeffrey F. Naughton.
international conference on management of data (1997)
Evaluating window joins over unbounded streams
J. Kang;J.F. Naughton;S.D. Viglas.
international conference on data engineering (2003)
Covering indexes for branching path queries
Raghav Kaushik;Philip Bohannon;Jeffrey F Naughton;Henry F Korth.
international conference on management of data (2002)
Materialized View Selection for Multidimensional Datasets
Amit Shukla;Prasad Deshpande;Jeffrey F. Naughton.
very large data bases (1998)
Profile was last updated on December 6th, 2021.
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