D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 30 Citations 12,903 92 World Ranking 8717 National Ranking 218

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Programming language
  • Database

His primary areas of study are Information retrieval, Artificial intelligence, Information extraction, WordNet and Knowledge base. His studies in Information retrieval integrate themes in fields like Ontology, Taxonomy, Web page and Binary relation. His studies deal with areas such as Field, Counterexample and Natural language processing as well as Artificial intelligence.

The concepts of his WordNet study are interwoven with issues in Ontology, Knowledge representation and reasoning, Infobox and Extension. His Infobox research is multidisciplinary, incorporating perspectives in Correctness and Knowledge extraction. His work in Knowledge base addresses subjects such as Query language, which are connected to disciplines such as Context, External Data Representation and Semantic search.

His most cited work include:

  • Yago: a core of semantic knowledge (2823 citations)
  • YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia (862 citations)
  • YAGO: A Large Ontology from Wikipedia and WordNet (670 citations)

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

Fabian M. Suchanek mostly deals with Information retrieval, World Wide Web, Knowledge base, Information extraction and Ontology. His Information retrieval research includes themes of Artificial intelligence, Knowledge representation and reasoning and Natural language processing. He has included themes like RDF and Data science in his Knowledge base study.

His Information extraction study which covers Knowledge extraction that intersects with Knowledge-based systems. His Ontology research is multidisciplinary, relying on both Ontology, Probabilistic logic and RDF Schema. His WordNet research integrates issues from Thesaurus, Dimension and Extension.

He most often published in these fields:

  • Information retrieval (41.79%)
  • World Wide Web (25.37%)
  • Knowledge base (22.39%)

What were the highlights of his more recent work (between 2016-2020)?

  • Information retrieval (41.79%)
  • Knowledge base (22.39%)
  • Web service (11.19%)

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

Fabian M. Suchanek mainly investigates Information retrieval, Knowledge base, Web service, Regular expression and Path. His research integrates issues of Rule mining and Template based in his study of Information retrieval. His Knowledge base study combines topics from a wide range of disciplines, such as Description logic, Software engineering and Web Ontology Language.

His biological study spans a wide range of topics, including Rewriting, Orchestration, If and only if and Service. The various areas that Fabian M. Suchanek examines in his Regular expression study include Precision and recall, Information extraction and Algebra. Information extraction is closely attributed to Theoretical computer science in his work.

Between 2016 and 2020, his most popular works were:

  • Predicting Completeness in Knowledge Bases (54 citations)
  • NeuroQuery: comprehensive meta-analysis of human brain mapping (25 citations)
  • YAGO 4: A Reason-able Knowledge Base (15 citations)

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

  • Artificial intelligence
  • Programming language
  • Database

His primary scientific interests are in Information retrieval, Knowledge base, Rule mining, Data mining and Completeness. Much of his study explores Information retrieval relationship to Template based. His work carried out in the field of Knowledge base brings together such families of science as Ontology, Web Ontology Language and Description logic.

The Rule mining study combines topics in areas such as Artificial neural network, Knowledge representation and reasoning and Semantic data mining. His study in Data mining is interdisciplinary in nature, drawing from both Correctness and Entity linking. Combining a variety of fields, including Completeness, Artificial intelligence, Spouse, Class and Natural language processing, are what the author presents in his essays.

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.

Best Publications

Yago: a core of semantic knowledge

Fabian M. Suchanek;Gjergji Kasneci;Gerhard Weikum.
the web conference (2007)

3682 Citations

YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia

Johannes Hoffart;Fabian M. Suchanek;Klaus Berberich;Gerhard Weikum.
Artificial Intelligence (2013)

1174 Citations

YAGO: A Large Ontology from Wikipedia and WordNet

Fabian M. Suchanek;Gjergji Kasneci;Gerhard Weikum.
Journal of Web Semantics (2008)

993 Citations

YAGO3: A Knowledge Base from Multilingual Wikipedias

Farzaneh Mahdisoltani;Joanna Biega;Fabian M. Suchanek.
conference on innovative data systems research (2014)

585 Citations

AMIE: association rule mining under incomplete evidence in ontological knowledge bases

Luis Antonio Galárraga;Christina Teflioudi;Katja Hose;Fabian Suchanek.
the web conference (2013)

446 Citations

PATTY: A Taxonomy of Relational Patterns with Semantic Types

Ndapandula Nakashole;Gerhard Weikum;Fabian Suchanek.
empirical methods in natural language processing (2012)

392 Citations

Fast rule mining in ontological knowledge bases with AMIE

Luis Galárraga;Christina Teflioudi;Katja Hose;Fabian M. Suchanek.
very large data bases (2015)

384 Citations

YAGO2: exploring and querying world knowledge in time, space, context, and many languages

Johannes Hoffart;Fabian M. Suchanek;Klaus Berberich;Edwin Lewis-Kelham.
the web conference (2011)

343 Citations

PARIS: probabilistic alignment of relations, instances, and schema

Fabian M. Suchanek;Serge Abiteboul;Pierre Senellart.
very large data bases (2011)

329 Citations

SOFIE: a self-organizing framework for information extraction

Fabian M. Suchanek;Mauro Sozio;Gerhard Weikum.
the web conference (2009)

314 Citations

Best Scientists Citing Fabian M. Suchanek

Gerhard Weikum

Gerhard Weikum

Max Planck Institute for Informatics

Publications: 185

Jens Lehmann

Jens Lehmann

University of Bonn

Publications: 63

Jiawei Han

Jiawei Han

University of Illinois at Urbana-Champaign

Publications: 52

Gerard de Melo

Gerard de Melo

Rutgers, The State University of New Jersey

Publications: 51

Heiko Paulheim

Heiko Paulheim

University of Mannheim

Publications: 51

Volker Tresp

Volker Tresp

Ludwig-Maximilians-Universität München

Publications: 43

Dongyan Zhao

Dongyan Zhao

Peking University

Publications: 37

Partha Pratim Talukdar

Partha Pratim Talukdar

Indian Institute of Science Bangalore

Publications: 36

Haixun Wang

Haixun Wang

Instacart

Publications: 34

Roberto Navigli

Roberto Navigli

Sapienza University of Rome

Publications: 31

Lei Chen

Lei Chen

Hong Kong University of Science and Technology

Publications: 29

Yangqiu Song

Yangqiu Song

Hong Kong University of Science and Technology

Publications: 28

Ralf Schenkel

Ralf Schenkel

University of Trier

Publications: 27

Andrew McCallum

Andrew McCallum

University of Massachusetts Amherst

Publications: 27

Jeff Z. Pan

Jeff Z. Pan

University of Edinburgh

Publications: 26

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

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