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.

People

Current Team:

Alumni:

Awards

Publications

2024

  • Peeters, R., Brinkmann, A. and Bizer, C. (2024). The Web Data Commons Schema.org Table Corpora. In , WWW '24 companion : companion proceedings of the ACM Web Conference 2024 (S. 1079-1082). , Association for Computing Machinery: New York, NY, United States.

2023

  • Bizer, C. (2023). GPT-4 versus BERT: Which foundation model is more suitable for integrating data from the web? WEBIST 2023, 19th International Conference on Web Information Systems and Technologies, Roma, Italy.
  • Bizer, C., Heath, T. and Berners-Lee, T. (2023). Linked data – the story so far. In Linking the world’s information: Essays on Tim Berners-Lee’s Invention of the World Wide Web (S. 115–143). New York: ACM Digital Library.
  • Brinkmann, A. (2023). Neural data search for table augmentation. In , Proceedings of the Workshops of the EDBT/ICDT 2023 Joint Conference, Ioannina, Greece, March, 28, 2023 (S. 1–4). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
  • Brinkmann, A., Primpeli, A. and Bizer, C. (2023). The Web Data Commons Schema.Org Data Set Series. In , The ACM Web Conference : Companion of the World Wide Web Conference WWW 2023 (S. 136–139). , Association for Computing Machinery: New York, NY.
  • Hassanzadeh, O., Abdelmageed, N., Efthymiou, V., Chen, J., Cutrona, V., Hulsebos, M., Jiménez-Ruiz, E., Khatiwada, A., Korini, K., Kruit, B., Sequeda, J. and Srinivas, K. (2023). Results of SemTab 2023. In , Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, SemTab 2023, co-located with the 22nd International Semantic Web Conference, ISWC 2023, Athens, Greece, November 6–10, 2023 (S. 1–14). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
  • Korini, K. and Bizer, C. (2023). Column type annotation using ChatGPT. In , Joint proceedings of workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28 – September 1, 2023, VLDBW 2023 (S. 1–12). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
  • Peeters, R. and Bizer, C. (2023). Using ChatGPT for Entity Matching. In , New Trends in Database and Information Systems : ADBIS 2023 short papers, doctoral consortium and workshops: AIDMA, DOING, K-Gals, MADEISD, PeRS, Barcelona, Spain, September 4–7, 2023, Proceedings (S. 221–230). Communications in Computer and Information Science, Springer: Cham.
  • Peeters, R., Der, R. C. and Bizer, C. (2023). WDC products: A multi-dimensional entity matching benchmark. In , Proceedings 27th International Conference on Extending Database Technology (EDBT 2024), Paestum, Italy, March 25 – March 28 (S. 22–33). OpenProceedings, OpenProceedings.org: Konstanz.

2022

2021

2020

2019

2018

  • Bizer, C., Vidal, M.-E. and Skaf-Molli, H. (2018). Linked Open Data. In , Encyclopedia of Database Systems (S. 2096-2101). New York, NY: Springer.
  • Bizer, C., Vidal, M.-E. and Weiss, M. (2018). RDF Technology. In , Encyclopedia of Database Systems (S. 3106-3109). New York, NY: Springer.
  • Bizer, C., Vidal, M.-E. and 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. and 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: Aachen, Germany.
  • Ristoski, P., Petrovski, P., Mika, P. and Paulheim, H. (2018). A machine learning approach for product matching and categorization. Semantic Web, 9, 707–728.

2017

2016

2015

2014