What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- World Wide Web
- Operating system
His primary areas of study are Semantic Web, Information retrieval, World Wide Web, Social Semantic Web and Semantic Web Stack.
Enrico Motta has included themes like Ontology, Semantic data model, Question answering and Knowledge engineering in his Semantic Web study.
His study looks at the relationship between World Wide Web and topics such as Variety, which overlap with Data integration, Ranking, Visual analytics and Sensemaking.
His studies deal with areas such as RDF, Search engine indexing and Semantic search as well as Social Semantic Web.
His Semantic Web Stack research incorporates elements of Semantic computing, Web 2.0 and Data Web.
His research integrates issues of User interface and Data science in his study of Ontology.
His most cited work include:
- The Semantic Web – ISWC 2005 (557 citations)
- Semantic annotation for knowledge management: Requirements and a survey of the state of the art (501 citations)
- Integrating Folksonomies with the Semantic Web (370 citations)
What are the main themes of his work throughout his whole career to date?
Enrico Motta mainly focuses on World Wide Web, Semantic Web, Information retrieval, Ontology and Social Semantic Web.
His study looks at the relationship between Semantic Web and fields such as Data science, as well as how they intersect with chemical problems.
Information retrieval is closely attributed to Natural language processing in his work.
Ontology is closely attributed to Ontology in his study.
The Social Semantic Web study combines topics in areas such as Web intelligence, Semantic Web Stack and Semantic search.
His Semantic Web Stack research is multidisciplinary, relying on both Semantic HTML, Semantic computing and Semantic grid.
He most often published in these fields:
- World Wide Web (38.25%)
- Semantic Web (36.18%)
- Information retrieval (33.87%)
What were the highlights of his more recent work (between 2016-2021)?
- Data science (14.29%)
- Ontology (32.49%)
- World Wide Web (38.25%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Data science, Ontology, World Wide Web, Artificial intelligence and Semantic Web.
His Data science research incorporates themes from Download, Variety, Semantic technology and Web application.
His Ontology study combines topics from a wide range of disciplines, such as Domain, Metadata, Knowledge base and Taxonomy.
His World Wide Web research is multidisciplinary, incorporating perspectives in Field and Workflow.
His Semantic Web study is focused on Information retrieval in general.
The study incorporates disciplines such as Cluster analysis and User requirements document in addition to Information retrieval.
Between 2016 and 2021, his most popular works were:
- The Computer Science Ontology: A Large-Scale Taxonomy of Research Areas (50 citations)
- AUGUR: Forecasting the Emergence of New Research Topics (23 citations)
- The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articles (20 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- World Wide Web
His primary scientific interests are in Data science, Ontology, Semantic Web, Research areas and Artificial intelligence.
His specific area of interest is Ontology, where he studies Ontology learning.
His Semantic Web research includes elements of Data access, Semantic data model, Top-down and bottom-up design, Strengths and weaknesses and Scientometrics.
Research areas is intertwined with Editorial team and World Wide Web in his research.
World Wide Web and Emerging technologies are commonly linked in his work.
The various areas that Enrico Motta examines in his Knowledge extraction study include Domain, Representation and Information retrieval.
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