What is he best known for?
The fields of study he is best known for:
- Programming language
- Artificial intelligence
- Algorithm
His main research concerns Theoretical computer science, Information retrieval, Query language, Functional dependency and Relational database.
He performs multidisciplinary study in Theoretical computer science and Forward chaining in his work.
His Information retrieval study combines topics in areas such as Ranking and Set.
His work carried out in the field of Query language brings together such families of science as Data modeling and Object model.
Expression is closely connected to Discrete mathematics in his research, which is encompassed under the umbrella topic of Relational database.
While the research belongs to areas of Join dependency, he spends his time largely on the problem of Chase, intersecting his research to questions surrounding Algorithm.
His most cited work include:
- The TSIMMIS Approach to Mediation: Data Models and Languages (806 citations)
- Magic Sets and Other Strange Ways to Implement Logic Programs. (618 citations)
- Answering Queries Using Views. (556 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Theoretical computer science, Discrete mathematics, Information retrieval, Algorithm and Query language.
His studies in Theoretical computer science integrate themes in fields like Functional dependency, Relational database, Conjunctive query, Set and Query optimization.
His study in Discrete mathematics is interdisciplinary in nature, drawing from both Dependency theory and Combinatorics.
His research in Information retrieval intersects with topics in Ranking and XML.
His XML research focuses on Semantics and how it relates to Probabilistic logic and Data mining.
His work deals with themes such as Data modeling, Pattern matching, Web query classification, RDF query language and Semantics, which intersect with Query language.
He most often published in these fields:
- Theoretical computer science (34.30%)
- Discrete mathematics (21.51%)
- Information retrieval (19.19%)
What were the highlights of his more recent work (between 2008-2017)?
- Information retrieval (19.19%)
- Theoretical computer science (34.30%)
- XML (12.79%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Information retrieval, Theoretical computer science, XML, Keyword search and Graph.
Yehoshua Sagiv combines subjects such as Ranking, Efficient XML Interchange and XML framework with his study of Information retrieval.
His research integrates issues of Set, Object, Probabilistic logic, Heuristic and Optimization problem in his study of Theoretical computer science.
His XML study often links to related topics such as Algorithm.
His work on Tree as part of general Algorithm study is frequently linked to Geo spatial, therefore connecting diverse disciplines of science.
Yehoshua Sagiv has researched Relational database in several fields, including Tuple and Negation.
Between 2008 and 2017, his most popular works were:
- On the expressiveness of probabilistic XML models (73 citations)
- Query evaluation over probabilistic XML (51 citations)
- Running tree automata on probabilistic XML (44 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Artificial intelligence
- Algorithm
Yehoshua Sagiv mainly investigates Theoretical computer science, Algorithm, Data mining, XML and Probabilistic logic.
In his study, Yehoshua Sagiv carries out multidisciplinary Theoretical computer science and Route planning software research.
His study on Tree structure is often connected to Geo spatial as part of broader study in Algorithm.
His Data mining research includes themes of Object, Preprocessor and Semantics.
His work in the fields of Document Structure Description overlaps with other areas such as Twig.
His Probabilistic logic study integrates concerns from other disciplines, such as Subspace topology, Data dependency, Aggregate, Probabilistic database and Data integrity.
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