H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 56 Citations 14,342 191 World Ranking 2048 National Ranking 1122

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • The Internet
  • Statistics

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 most cited work include:

  • DBXplorer: a system for keyword-based search over relational databases (731 citations)
  • Rule discovery from time series (596 citations)
  • On sparse spanners of weighted graphs (485 citations)

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

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.

He most often published in these fields:

  • Data mining (25.17%)
  • Information retrieval (19.39%)
  • Database (15.99%)

What were the highlights of his more recent work (between 2014-2021)?

  • Tuple (12.59%)
  • Data mining (25.17%)
  • Artificial intelligence (10.20%)

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

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

  • Web search query, which have a strong connection to Query expansion,
  • Function and related Set and Mathematical optimization. His Set study integrates concerns from other disciplines, such as Theoretical computer science and Approximation algorithm. His Interface research focuses on Graph and how it connects with World Wide Web.

Between 2014 and 2021, his most popular works were:

  • Everything You Wanted to Know About the Blockchain: Its Promise, Components, Processes, and Problems (105 citations)
  • Task assignment optimization in knowledge-intensive crowdsourcing (84 citations)
  • Designing Fair Ranking Schemes (45 citations)

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

  • Artificial intelligence
  • The Internet
  • Statistics

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.

Top Publications

DBXplorer: enabling keyword search over relational databases

Sanjay Agrawal;Surajit Chaudhuri;Gautam Das.
international conference on management of data (2002)

1161 Citations

DBXplorer: a system for keyword-based search over relational databases

S. Agrawal;S. Chaudhuri;G. Das.
international conference on data engineering (2002)

1006 Citations

Rule discovery from time series

Gautam Das;King-Ip Lin;Heikki Mannila;Gopal Renganathan.
knowledge discovery and data mining (1998)

957 Citations

On sparse spanners of weighted graphs

Ingo Althöfer;Gautam Das;David Dobkin;Deborah Joseph.
Discrete and Computational Geometry (1993)

589 Citations

Finding Similar Time Series

Gautam Das;Dimitrios Gunopulos;Heikki Mannila.
european conference on principles of data mining and knowledge discovery (1997)

447 Citations

Group recommendation: semantics and efficiency

Sihem Amer-Yahia;Senjuti Basu Roy;Ashish Chawlat;Gautam Das.
very large data bases (2009)

384 Citations

Automated Ranking of Database Query Results

Sanjay Agrawal;Surajit Chaudhuri;Gautam Das;Aristides Gionis.
conference on innovative data systems research (2003)

340 Citations

Dynamic sample selection for approximate query processing

Brian Babcock;Surajit Chaudhuri;Gautam Das.
international conference on management of data (2003)

309 Citations

The Discrete Basis Problem

P. Miettinen;T. Mielikainen;A. Gionis;G. Das.
IEEE Transactions on Knowledge and Data Engineering (2008)

276 Citations

Regulation and Function of Autophagy during Cell Survival and Cell Death

Gautam Das;Bhupendra V. Shravage;Eric H. Baehrecke.
Cold Spring Harbor Perspectives in Biology (2012)

267 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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