Gautam Das mostly deals with Data mining, Information retrieval, Ranking, Combinatorics and Sampling. His Data mining research integrates issues from Optimization problem, Sample, Key and Probabilistic logic. His Information retrieval research incorporates themes from Tuple and Data structure.
His work carried out in the field of Ranking brings together such families of science as Monotone polygon, Relation, Database, Function and View. His research integrates issues of Discrete mathematics and Spanner in his study of Combinatorics. The various areas that Gautam Das examines in his Query language study include World Wide Web, Search engine, User interface, File server and Web server.
His primary areas of investigation include Data mining, Information retrieval, Database, Tuple and Ranking. His Data mining study combines topics in areas such as Sampling, Probabilistic logic, Set and Sample. He frequently studies issues relating to World Wide Web and Information retrieval.
The concepts of his Database study are interwoven with issues in User interface and Data Web. His biological study spans a wide range of topics, including Location-based service, Pruning, Interface, Search engine indexing and Skyline. His research in Ranking intersects with topics in Function and Rank.
His main research concerns Tuple, Data mining, Artificial intelligence, Database and Ranking. His Tuple research is multidisciplinary, incorporating elements of Ranking, Information retrieval, Location-based service, Point and Skyline. His research on Data mining focuses in particular on Aggregate.
His Ranking study also includes
Gautam Das mainly investigates Data mining, Approximation algorithm, Ranking, Crowdsourcing and Task. His research related to Relational database and Query optimization might be considered part of Data mining. As a part of the same scientific study, Gautam Das usually deals with the Approximation algorithm, concentrating on Set and frequently concerns with Sample size determination and Data analysis.
His work deals with themes such as Mathematical optimization, Function, Search engine indexing, Robustness and Operations research, which intersect with Ranking. His Search engine indexing study is related to the wider topic of Information retrieval. His Crowdsourcing research is multidisciplinary, incorporating perspectives in Sentence and Data science.
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.
DBXplorer: enabling keyword search over relational databases
Sanjay Agrawal;Surajit Chaudhuri;Gautam Das.
international conference on management of data (2002)
DBXplorer: a system for keyword-based search over relational databases
S. Agrawal;S. Chaudhuri;G. Das.
international conference on data engineering (2002)
Rule discovery from time series
Gautam Das;King-Ip Lin;Heikki Mannila;Gopal Renganathan.
knowledge discovery and data mining (1998)
On sparse spanners of weighted graphs
Ingo Althöfer;Gautam Das;David Dobkin;Deborah Joseph.
Discrete and Computational Geometry (1993)
Finding Similar Time Series
Gautam Das;Dimitrios Gunopulos;Heikki Mannila.
european conference on principles of data mining and knowledge discovery (1997)
Group recommendation: semantics and efficiency
Sihem Amer-Yahia;Senjuti Basu Roy;Ashish Chawlat;Gautam Das.
very large data bases (2009)
The Discrete Basis Problem
P. Miettinen;T. Mielikainen;A. Gionis;G. Das.
IEEE Transactions on Knowledge and Data Engineering (2008)
Automated Ranking of Database Query Results
Sanjay Agrawal;Surajit Chaudhuri;Gautam Das;Aristides Gionis.
conference on innovative data systems research (2003)
Dynamic sample selection for approximate query processing
Brian Babcock;Surajit Chaudhuri;Gautam Das.
international conference on management of data (2003)
Optimized stratified sampling for approximate query processing
Surajit Chaudhuri;Gautam Das;Vivek Narasayya.
ACM Transactions on Database Systems (2007)
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