H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 58 Citations 36,865 135 World Ranking 1773 National Ranking 74

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • World Wide Web
  • Programming language

Christian Bizer mainly investigates World Wide Web, Linked data, Semantic Web, Information retrieval and RDF. Specifically, his work in World Wide Web is concerned with the study of Table of contents. In his study, SIMPLE, Protocol and Data warehouse is inextricably linked to Data mapping, which falls within the broad field of Linked data.

Christian Bizer focuses mostly in the field of Semantic Web, narrowing it down to matters related to Data Web and, in some cases, Web modeling and Web standards. His study explores the link between Information retrieval and topics such as Set that cross with problems in Metadata and Web crawler. His work in RDF addresses issues such as Data model, which are connected to fields such as Graph.

His most cited work include:

  • Linked Data - the story so far (3943 citations)
  • DBpedia: a nucleus for a web of open data (3122 citations)
  • DBpedia - A crystallization point for the Web of Data (1641 citations)

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

Christian Bizer spends much of his time researching World Wide Web, Linked data, Information retrieval, Semantic Web and RDF. World Wide Web is represented through his Data Web, Semantic Web Stack, Social Semantic Web, Web standards and Web page research. His study in Linked data is interdisciplinary in nature, drawing from both Set, Data mapping and Data mining, Data model.

His research in Information retrieval intersects with topics in Web tables, Microdata, Data integration and Knowledge base. His Semantic Web research integrates issues from Knowledge management, Search engine and Data science. Christian Bizer has included themes like Relational database, Web crawler and Workflow in his RDF study.

He most often published in these fields:

  • World Wide Web (57.05%)
  • Linked data (39.74%)
  • Information retrieval (39.10%)

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

  • Information retrieval (39.10%)
  • Artificial intelligence (8.33%)
  • Machine learning (5.77%)

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

His primary areas of investigation include Information retrieval, Artificial intelligence, Machine learning, Knowledge base and Data mining. His work carried out in the field of Information retrieval brings together such families of science as Sentiment analysis, Binary relation, Annotation, Web tables and Extension. Christian Bizer works mostly in the field of Artificial intelligence, limiting it down to concerns involving Product and, occasionally, Data model and Benchmark.

His Knowledge base research is multidisciplinary, incorporating elements of Table and Schema matching. In his works, he performs multidisciplinary study on Amazon web services and World Wide Web. His biological study spans a wide range of topics, including Product description, Column and Supervised learning.

Between 2016 and 2020, his most popular works were:

  • Matching web tables to DBpedia - a feature utility study (35 citations)
  • Stitching web tables for improving matching quality (29 citations)
  • Extracting attribute-value pairs from product specifications on the web (10 citations)

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

  • Artificial intelligence
  • Programming language
  • World Wide Web

His scientific interests lie mostly in Information retrieval, Schema matching, Data mining, Knowledge base and Web page. His study in the field of Question answering is also linked to topics like Selection. His studies in Data mining integrate themes in fields like Feature, Artificial intelligence and Benchmark.

His Knowledge base research includes themes of Domain knowledge, Extension, Exploit, Table and Table. His work deals with themes such as Base, Image stitching, Process and Binary relation, which intersect with Table. His Web page study introduces a deeper knowledge of World Wide Web.

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

Linked Data - the story so far

Christian Bizer;Tom Heath;Tim Berners-Lee.
International Journal on Semantic Web and Information Systems (2009)

6904 Citations

DBpedia: a nucleus for a web of open data

Sören Auer;Christian Bizer;Georgi Kobilarov;Jens Lehmann.
international semantic web conference (2007)

5018 Citations

Linked Data: Evolving the Web into a Global Data Space

Tom Heath;Christian Bizer;Bebo White.
(2011)

3173 Citations

DBpedia - A crystallization point for the Web of Data

Christian Bizer;Jens Lehmann;Georgi Kobilarov;Sören Auer.
Journal of Web Semantics (2009)

2670 Citations

DBpedia - A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia

Jens Lehmann;Robert Isele;Max Jakob;Anja Jentzsch.
Social Work (2015)

2236 Citations

Linked Data

Tom Heath;Christian Bizer;James Hendler.
(2011)

1736 Citations

DBpedia spotlight: shedding light on the web of documents

Pablo N. Mendes;Max Jakob;Andrés García-Silva;Christian Bizer.
international conference on semantic systems (2011)

1289 Citations

The Berlin SPARQL benchmark

Christian Bizer;Andreas Schultz.
International Journal on Semantic Web and Information Systems (2009)

801 Citations

Named graphs, provenance and trust

Jeremy J. Carroll;Christian Bizer;Pat Hayes;Patrick Stickler.
the web conference (2005)

791 Citations

Linked data on the web (LDOW2008)

Christian Bizer;Tom Heath;Kingsley Idehen;Tim Berners-Lee.
the web conference (2008)

572 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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