What is he best known for?
The fields of study he is best known for:
- The Internet
- Artificial intelligence
- Operating system
The scientist’s investigation covers issues in World Wide Web, Semantic Web, Social Semantic Web, Social web and Semantic Web Stack.
His studies deal with areas such as User experience design and Computer user satisfaction, User modeling as well as World Wide Web.
As a member of one scientific family, he mostly works in the field of Semantic Web, focusing on Ontology and, on occasion, Folksonomy, Online community and RDF.
Social media is closely connected to Order in his research, which is encompassed under the umbrella topic of Social Semantic Web.
As part of one scientific family, John G. Breslin deals mainly with the area of Social web, narrowing it down to issues related to the Internet privacy, and often Ubiquitous computing.
His research integrates issues of Web standards, Web modeling and Data Web in his study of Semantic Web Stack.
His most cited work include:
- Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples (334 citations)
- Optimizing the AC resistance of multilayer transformer windings with arbitrary current waveforms (277 citations)
- Towards semantically-interlinked online communities (229 citations)
What are the main themes of his work throughout his whole career to date?
John G. Breslin spends much of his time researching World Wide Web, Semantic Web, Social Semantic Web, Information retrieval and Social web.
As part of the same scientific family, John G. Breslin usually focuses on World Wide Web, concentrating on Semantics and intersecting with Content management.
His work in Semantic Web addresses issues such as Ontology, which are connected to fields such as Semantic data model.
The study incorporates disciplines such as Web standards, Web development, Web 2.0 and Data Web in addition to Social Semantic Web.
His Information retrieval study combines topics from a wide range of disciplines, such as Metadata and Cloud computing.
John G. Breslin has included themes like Internet privacy and Social network in his Social web study.
He most often published in these fields:
- World Wide Web (48.79%)
- Semantic Web (33.06%)
- Social Semantic Web (19.76%)
What were the highlights of his more recent work (between 2016-2021)?
- Computer network (3.63%)
- Artificial intelligence (8.47%)
- Scalability (3.63%)
In recent papers he was focusing on the following fields of study:
John G. Breslin focuses on Computer network, Artificial intelligence, Scalability, Blockchain and Peer-to-peer.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Domain, Machine learning and Analytics.
His work in Peer-to-peer addresses subjects such as Prosumer, which are connected to disciplines such as Structure, Duration, Adversarial system and Co-simulation.
John G. Breslin performs integrative Irish and World Wide Web research in his work.
As a part of the same scientific family, John G. Breslin mostly works in the field of World Wide Web, focusing on Profiling and, on occasion, Linked data.
Specifically, his work in Information retrieval is concerned with the study of Semantic Web.
Between 2016 and 2021, his most popular works were:
- Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case (50 citations)
- RDF dataset profiling – a survey of features, methods, vocabularies and applications (41 citations)
- Co-simulation of electricity distribution networks and peer to peer energy trading platforms (33 citations)
In his most recent research, the most cited papers focused on:
- The Internet
- Artificial intelligence
- Operating system
John G. Breslin mainly focuses on Artificial intelligence, Peer-to-peer, Blockchain, Recommender system and Edge device.
The various areas that he examines in his Artificial intelligence study include Domain and Machine learning.
His biological study spans a wide range of topics, including Network planning and design and Prosumer.
His Blockchain study which covers Microgrid that intersects with Internet privacy and Energy trading.
His study in Recommender system is interdisciplinary in nature, drawing from both Embedding, User modeling, Knowledge base and Natural language processing.
His User modeling research integrates issues from Social media, World Wide Web, Personalization, Dimension and Focus.
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