What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Algorithm
Grigoris Antoniou focuses on Defeasible logic, Artificial intelligence, Semantic Web, Ontology and Non-monotonic logic.
His research in Artificial intelligence tackles topics such as Argumentation theory which are related to areas like Rule of inference, Executable and Agent architecture.
His research investigates the link between Semantic Web and topics such as Description logic that cross with problems in Ontology, Knowledge base and Belief revision.
His Non-monotonic logic study integrates concerns from other disciplines, such as Defeasible estate, Default logic and Logic programming.
The concepts of his Defeasible reasoning study are interwoven with issues in Programming language and Reasoning system.
He has included themes like Ontology-based data integration and World Wide Web in his Upper ontology study.
His most cited work include:
- A semantic Web primer (1213 citations)
- Web Ontology Language: OWL (753 citations)
- Nonmonotonic Reasoning (485 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Semantic Web, Theoretical computer science, Non-monotonic logic and Defeasible logic.
He has researched Artificial intelligence in several fields, including Context, Machine learning and Natural language processing.
The Semantic Web study which covers Ontology that intersects with Semantics and Ontology.
His research integrates issues of Negation and Knowledge representation and reasoning in his study of Theoretical computer science.
His Non-monotonic logic research includes elements of Default logic, Circumscription and Complete information.
His Defeasible logic study incorporates themes from Defeasible reasoning and Argumentation theory.
He most often published in these fields:
- Artificial intelligence (33.24%)
- Semantic Web (29.70%)
- Theoretical computer science (22.89%)
What were the highlights of his more recent work (between 2012-2021)?
- Semantic Web (29.70%)
- Theoretical computer science (22.89%)
- Artificial intelligence (33.24%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Semantic Web, Theoretical computer science, Artificial intelligence, Ontology and Natural language.
His Semantic Web research entails a greater understanding of World Wide Web.
Grigoris Antoniou combines subjects such as Semantics, Axiom, Semantics and RDF with his study of Theoretical computer science.
The study incorporates disciplines such as Machine learning and Natural language processing in addition to Artificial intelligence.
His Ontology study is concerned with Information retrieval in general.
His biological study spans a wide range of topics, including Non-monotonic logic and Well-founded semantics.
Between 2012 and 2021, his most popular works were:
- Ontology evolution: a process-centric survey (91 citations)
- Supply chain risk management and artificial intelligence: state of the art and future research directions (85 citations)
- ELIMINATING CONCEPTS AND ROLES FROM ONTOLOGIES IN EXPRESSIVE DESCRIPTIVE LOGICS (28 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Algorithm
His primary areas of study are Artificial intelligence, Semantic Web, Ontology, Scalability and Theoretical computer science.
His work deals with themes such as Machine learning and Natural language processing, which intersect with Artificial intelligence.
Grigoris Antoniou is investigating World Wide Web and Information retrieval as part of his examination of Semantic Web.
His World Wide Web research is multidisciplinary, relying on both Semantics, Logical consequence, Data hub and Field.
His studies in Scalability integrate themes in fields like Hash function, Semantics, Logic programming and Big data.
His Theoretical computer science research is multidisciplinary, incorporating perspectives in Relational model, Relational database and Programming language.
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