H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 73 Citations 24,590 291 World Ranking 686 National Ranking 26

Overview

What is he best known for?

The fields of study he is best known for:

  • The Internet
  • World Wide Web
  • Artificial intelligence

Stefan Decker mostly deals with World Wide Web, Semantic Web, RDF, Social Semantic Web and Information retrieval. His study in World Wide Web concentrates on Web standards, Social web, OWL-S, Information needs and Semantic search. Stefan Decker studied Web standards and Web development that intersect with Web 2.0.

His biological study spans a wide range of topics, including Schema, Semantics, The Internet and Service. The various areas that he examines in his RDF study include Ontology, Metadata, Knowledge representation and reasoning, XML and Linked data. His studies deal with areas such as Web modeling, Semantic Web Stack and Data Web as well as Social Semantic Web.

His most cited work include:

  • Creating Semantic Web contents with Protege-2000 (888 citations)
  • Description Logic Programs: Combining Logic Programs with Description Logic (784 citations)
  • EDUTELLA: a P2P networking infrastructure based on RDF (765 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are World Wide Web, Semantic Web, Information retrieval, Social Semantic Web and Semantic Web Stack. His work in Data Web, Web standards, Linked data, RDF and Web modeling is related to World Wide Web. Stefan Decker usually deals with RDF and limits it to topics linked to Knowledge representation and reasoning and Description logic.

As a member of one scientific family, Stefan Decker mostly works in the field of Semantic Web, focusing on Ontology and, on occasion, The Internet. His Social Semantic Web research includes themes of Social web and Knowledge management. His work deals with themes such as Semantic computing and Semantic grid, which intersect with Semantic Web Stack.

He most often published in these fields:

  • World Wide Web (56.43%)
  • Semantic Web (42.69%)
  • Information retrieval (28.95%)

What were the highlights of his more recent work (between 2011-2017)?

  • Linked data (21.05%)
  • World Wide Web (56.43%)
  • SPARQL (14.04%)

In recent papers he was focusing on the following fields of study:

Stefan Decker spends much of his time researching Linked data, World Wide Web, SPARQL, Information retrieval and RDF. His Linked data research is included under the broader classification of Semantic Web. His work on Social Semantic Web and Semantic Web Stack is typically connected to Political science as part of general Semantic Web study, connecting several disciplines of science.

Stefan Decker works in the field of World Wide Web, focusing on Semantic technology in particular. His Information retrieval study incorporates themes from Schema, Graph and Data integration. His RDF research integrates issues from Metadata, Knowledge representation and reasoning, Object, Access control and XML.

Between 2011 and 2017, his most popular works were:

  • An empirical survey of Linked Data conformance (146 citations)
  • MAPPING BETWEEN RDF AND XML WITH XSPARQL (91 citations)
  • Scalable and distributed methods for entity matching, consolidation and disambiguation over linked data corpora (74 citations)

In his most recent research, the most cited papers focused on:

  • The Internet
  • World Wide Web
  • Artificial intelligence

Stefan Decker mainly investigates Linked data, Information retrieval, SPARQL, Semantic Web and RDF. The subject of his Linked data research is within the realm of World Wide Web. His World Wide Web study combines topics from a wide range of disciplines, such as User interface and Workflow.

His research investigates the connection between SPARQL and topics such as Database that intersect with issues in Data cube. His work investigates the relationship between Semantic Web and topics such as Data integration that intersect with problems in Interface and Parsing. His research integrates issues of XML, Search engine indexing and Access control in his study of RDF.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Creating Semantic Web contents with Protege-2000

N.F. Noy;M. Sintek;S. Decker;M. Crubezy.
IEEE Intelligent Systems (2001)

1498 Citations

Description logic programs: combining logic programs with description logic

Benjamin N. Grosof;Ian Horrocks;Raphael Volz;Stefan Decker.
the web conference (2003)

1314 Citations

EDUTELLA: a P2P networking infrastructure based on RDF

Wolfgang Nejdl;Boris Wolf;Changtao Qu;Stefan Decker.
the web conference (2002)

1212 Citations

The Semantic Web: the roles of XML and RDF

S. Decker;S. Melnik;F. van Harmelen;D. Fensel.
IEEE Internet Computing (2000)

1178 Citations

The Semantic Web - ISWC 2006

Isabel Cruz;Stefan Decker;Dean Allemang;Chris Preist.
(2006)

1003 Citations

Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information

Stefan Decker;Michael Erdmann;Dieter Fensel;Rudi Studer.
discovery science (1999)

838 Citations

OIL in a Nutshell

Dieter Fensel;Ian Horrocks;Frank van Harmelen;Stefan Decker.
knowledge acquisition modeling and management (2000)

666 Citations

TRIPLE - A Query, Inference, and Transformation Language for the Semantic Web

Michael Sintek;Stefan Decker.
international semantic web conference (2002)

543 Citations

YARS2: a federated repository for querying graph structured data from the web

Andreas Harth;Jürgen Umbrich;Aidan Hogan;Stefan Decker.
international semantic web conference (2007)

364 Citations

Optimized index structures for querying RDF from the Web

A. Harth;S. Decker.
latin american web congress (2005)

363 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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