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.
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