Focus Group: Web-based Systems

(Prof. Bizer)

We explore technical and empirical questions concerning the development of global, decentralized information environments. Our current focus is the evolution of the World Wide Web from a medium for the publication of documents into a global dataspace. Our empirical work is accompanying this evolution by monitoring the adoption of Semantic Markup and Linked Data technologies on the Web. Our technical work focuses on integrating data from large numbers of Web data sources and includes topics such as information extraction, identity resolution, schema matching, data fusion, and data search. We apply the developed methods for the tasks of integrating product data from large numbers of e-shops as well as for creating large-scale knowledge bases such as DBpedia.


Current Team:


  • Dr. Yaser Oulabi (2020)
  • Dr. Oliver Lehmberg (2019)
  • Benedikt Kleppmann (2018)
  • Dr. Dominique Ritze (2017)
  • Petar Petrovski (2017)
  • Dr. Anna Lisa Gentile (2017)
  • Dr. Robert Meusel (2016)
  • Prof. Dr. Kai Eckert (2015)
  • Dr. Volha Bryl (2015)
  • Max Schlachtenberg (2014)
  • Dr. Robert Isele (2013)




  • Peeters, R. und Bizer, C. (2021). Dual-objective fine-tuning of BERT for entity matching. In , 47th International Conference on Very Large Data Bases (VLDB 2021) : Copenhagen, Denmark, August 16-20, 2021 (S. 1913-1921). Proceedings of the VLDB Endowment, Association of Computing Machinery: New York, NY.




  • Bizer, C., Vidal, M.-E. und Skaf-Molli, H. (2018). Linked Open Data. In , Encyclopedia of Database Systems (S. 2096-2101). New York, NY: Springer.
  • Bizer, C., Vidal, M.-E. und Weiss, M. (2018). RDF Technology. In , Encyclopedia of Database Systems (S. 3106-3109). New York, NY: Springer.
  • Bizer, C., Vidal, M.-E. und Weiss, M. (2018). Resource Description Framework. In , Encyclopedia of Database Systems (S. 3221-3224). New York, NY: Springer.
  • Kleppmann, B., Bizer, C., Yaqub, E., Temme, F., Schlunder, P., Arnu, D. und Klinkenberg, R. (2018). Density- and correlation-based table extension. In , LWDA 2018 : Proceedings of the Conference „Lernen, Wissen, Daten, Analysen“ Mannheim, Germany, August 22-24, 2018 (S. 191-194). CEUR Workshop Proceedings, RWTH: Aachen.
  • Ristoski, P., Petrovski, P., Mika, P. und Paulheim, H. (2018). A machine learning approach for product matching and categorization. Semantic Web, 9, 707-728.