What is he best known for?
The fields of study he is best known for:
- Programming language
- Artificial intelligence
- Ontology
His primary areas of investigation include Ontology, Information retrieval, Theoretical computer science, Description logic and Web Ontology Language.
His OWL-S, Process ontology and Ontology language study, which is part of a larger body of work in Ontology, is frequently linked to Ontology, bridging the gap between disciplines.
His study in the fields of Open Biomedical Ontologies and Ontology alignment under the domain of Information retrieval overlaps with other disciplines such as Empirical evidence.
Bernardo Cuenca Grau has researched Description logic in several fields, including Semantic reasoner and Conservative extension.
He combines subjects such as Programming language and Axiom with his study of Semantic reasoner.
Bernardo Cuenca Grau works mostly in the field of Web Ontology Language, limiting it down to topics relating to Conjunctive query and, in certain cases, Middleware, Abox, Java and Debugging.
His most cited work include:
- Pellet: A practical OWL-DL reasoner (2095 citations)
- OWL 2: The next step for OWL (693 citations)
- OWL 2 Web Ontology Language: Profiles (360 citations)
What are the main themes of his work throughout his whole career to date?
Bernardo Cuenca Grau spends much of his time researching Ontology, Information retrieval, Web Ontology Language, Description logic and Theoretical computer science.
His work in the fields of Ontology, such as Ontology language, overlaps with other areas such as Ontology.
The various areas that Bernardo Cuenca Grau examines in his Web Ontology Language study include Programming language and Conjunctive query.
His Description logic research integrates issues from Axiom, Calculus and Knowledge representation and reasoning.
His Theoretical computer science research is multidisciplinary, incorporating elements of Set, Logical consequence and Scalability.
In general Semantic Web, his work in Semantic Web Rule Language and Semantic Web Stack is often linked to Information system linking many areas of study.
He most often published in these fields:
- Ontology (47.72%)
- Information retrieval (31.98%)
- Web Ontology Language (30.96%)
What were the highlights of his more recent work (between 2016-2021)?
- Datalog (18.78%)
- Theoretical computer science (24.87%)
- Information retrieval (31.98%)
In recent papers he was focusing on the following fields of study:
Bernardo Cuenca Grau mainly focuses on Datalog, Theoretical computer science, Information retrieval, Description logic and Discrete mathematics.
His research investigates the link between Theoretical computer science and topics such as Scalable algorithms that cross with problems in Similarity.
Ontology, RDF and SPARQL are the core of his Information retrieval study.
His studies in Ontology integrate themes in fields like Data access, Data integrity and Tuple.
His Tuple research includes elements of Ontology language and Conjunctive query.
Bernardo Cuenca Grau connects Description logic with Pay as you go in his study.
Between 2016 and 2021, his most popular works were:
- Logical foundations of information disclosure in ontology−based data integration (17 citations)
- Semantic Faceted Search with Aggregation and Recursion (14 citations)
- Query Nesting, Assignment, and Aggregation in SPARQL 1.1 (12 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Artificial intelligence
- Algorithm
The scientist’s investigation covers issues in Information retrieval, Datalog, Extension, RDF and Semantics.
His work carried out in the field of Information retrieval brings together such families of science as Global schema and Data integration.
His study on Datalog is covered under Programming language.
His research integrates issues of Context, Set and Faceted search in his study of RDF.
His Context study combines topics from a wide range of disciplines, such as Theoretical computer science and Recursion.
His studies deal with areas such as Ontology, Conjunctive query, Tuple, Analytics and Nesting as well as Semantics.
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