What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Database
World Wide Web, Information retrieval, Semantic Web, Semantic Web Stack and Social Semantic Web are his primary areas of study.
Amit P. Sheth regularly ties together related areas like Metadata in his Information retrieval studies.
Amit P. Sheth has included themes like Ontology and Information extraction in his Semantic Web study.
The Ontology study combines topics in areas such as Semantics and Data science.
He studies Semantic Web Stack, focusing on Semantic analytics in particular.
His studies examine the connections between Social Semantic Web and genetics, as well as such issues in Semantic grid, with regards to Semantic computing.
His most cited work include:
- Federated database systems for managing distributed, heterogeneous, and autonomous databases (2326 citations)
- An overview of workflow management: from process modeling to workflow automation infrastructure (1490 citations)
- Ontology paper: The SSN ontology of the W3C semantic sensor network incubator group (951 citations)
What are the main themes of his work throughout his whole career to date?
Amit P. Sheth mainly investigates World Wide Web, Information retrieval, Semantic Web, Social Semantic Web and Semantic Web Stack.
His research on World Wide Web often connects related topics like Semantics.
His Information retrieval study frequently draws connections between related disciplines such as Metadata.
His Semantic Web study frequently links to adjacent areas such as Interoperability.
His Semantic Web Stack study incorporates themes from Semantic computing, Semantic grid, Semantic interoperability and Semantic search.
His study explores the link between Ontology and topics such as Data science that cross with problems in Social media.
He most often published in these fields:
- World Wide Web (36.32%)
- Information retrieval (26.16%)
- Semantic Web (25.09%)
What were the highlights of his more recent work (between 2013-2020)?
- World Wide Web (36.32%)
- Social media (7.53%)
- Information retrieval (26.16%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are World Wide Web, Social media, Information retrieval, Data science and Artificial intelligence.
His research on World Wide Web often connects related areas such as Semantics.
His study in the field of Microblogging also crosses realms of Public opinion.
His Information retrieval study combines topics in areas such as Structure and Categorization.
His work deals with themes such as Variety, Health care, Public health and Big data, which intersect with Data science.
His Artificial intelligence study also includes fields such as
- Natural language processing which intersects with area such as Query expansion,
- Domain that intertwine with fields like Ontology.
Between 2013 and 2020, his most popular works were:
- Machine Learning for Internet of Things Data Analysis: A Survey (299 citations)
- Semantic Gateway as a Service Architecture for IoT Interoperability (167 citations)
- User Interests Identification on Twitter Using a Hierarchical Knowledge Base (100 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Operating system
Amit P. Sheth spends much of his time researching World Wide Web, Social media, Data science, Information retrieval and The Internet.
His studies deal with areas such as Intelligent decision support system, Semantics and Variety as well as World Wide Web.
Amit P. Sheth combines subjects such as Digital health, Health care, Domain knowledge, Knowledge management and Public health with his study of Data science.
RDF and Semantic Web are the core of his Information retrieval study.
His research ties Ontology and Semantic Web together.
His The Internet research is multidisciplinary, relying on both Classifier, Data quality and Internet privacy.
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