What is he best known for?
The fields of study he is best known for:
- Database
- Operating system
- Programming language
Jayant R. Haritsa focuses on Distributed computing, Data mining, Database transaction, Query optimization and Scheduling.
His Distributed computing study frequently draws connections to adjacent fields such as Serializability.
His Serializability study incorporates themes from Multiversion concurrency control, Distributed concurrency control, Non-lock concurrency control, Optimistic concurrency control and Isolation.
His Data mining research includes elements of Range, Intersection and Information privacy.
His studies examine the connections between Database transaction and genetics, as well as such issues in Commit, with regards to Atomic commit, Distributed transaction, Distributed database, Two-phase commit protocol and Compensating transaction.
As a part of the same scientific family, he mostly works in the field of Query optimization, focusing on Sargable and, on occasion, Benchmark, View, Query language and Theoretical computer science.
His most cited work include:
- Maintaining data privacy in association rule mining (453 citations)
- XGrind: a query-friendly XML compressor (248 citations)
- Turbo-charging vertical mining of large databases (246 citations)
What are the main themes of his work throughout his whole career to date?
Jayant R. Haritsa spends much of his time researching Database, Data mining, Distributed computing, Query optimization and Information retrieval.
His Data mining research is multidisciplinary, incorporating perspectives in Process, Theoretical computer science and Set.
The Distributed computing study combines topics in areas such as Serializability, Distributed transaction, Database transaction, Transaction processing and Concurrency control.
His study explores the link between Serializability and topics such as Optimistic concurrency control that cross with problems in Multiversion concurrency control and Isolation.
The study incorporates disciplines such as Query language, Query expansion and Web query classification, Online aggregation, Sargable in addition to Query optimization.
His Information retrieval research integrates issues from XML database, XML validation, XML, XML framework and Simple API for XML.
He most often published in these fields:
- Database (31.33%)
- Data mining (26.00%)
- Distributed computing (22.00%)
What were the highlights of his more recent work (between 2012-2021)?
- Distributed computing (22.00%)
- Information retrieval (14.00%)
- Query optimization (19.33%)
In recent papers he was focusing on the following fields of study:
Jayant R. Haritsa mainly investigates Distributed computing, Information retrieval, Query optimization, Process and Data mining.
His research investigates the connection with Distributed computing and areas like Big data which intersect with concerns in Scalability, Software deployment and Data management.
His Query optimization study is concerned with the field of Database as a whole.
His work carried out in the field of Database brings together such families of science as Hash table and Implementation.
His studies deal with areas such as Online analytical processing and Benchmark as well as Process.
He merges many fields, such as Data mining and Size reduction, in his writings.
Between 2012 and 2021, his most popular works were:
- Plan bouquets: query processing without selectivity estimation (30 citations)
- Securely processing range predicates on cloud databases (12 citations)
- Plan Bouquets: A Fragrant Approach to Robust Query Processing (11 citations)
In his most recent research, the most cited papers focused on:
- Database
- Operating system
- Programming language
His primary areas of investigation include Distributed computing, Data mining, Process, Set and Query expansion.
His Distributed computing research incorporates themes from Utility computing, Cloud computing security, Online analytical processing and Benchmark.
His research in Data mining is mostly concerned with Query optimization.
His Query optimization study frequently draws connections between adjacent fields such as Query language.
His Set research is multidisciplinary, incorporating elements of Domain, Range query, Range and Plain text, Encryption.
His study in Query expansion is interdisciplinary in nature, drawing from both Web search query, Sargable, Artificial intelligence and Natural language processing.
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