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Norman Meuschke

Chair of Digital Media
University of Wuppertal
School of Electrical
Information and Media Engineering
Rainer-Gruenter-Str. 21
D-42119 Wuppertal
Office: FC 1.19

Phone: +49 (0)202 439 1618


Norman Meuschke

Doctoral Researcher

Office: FC 1.19

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Research Interests

My main research interests are methods for semantic similarity analysis and their application for information retrieval. Beyond my core research, I am interested in applied data science and knowledge management challenges and the application of blockchain technology to tackle these challenges.

My research spans the fields of:

  • Information Retrieval for text, images, and mathematical content
  • Plagiarism Detection
  • Citation and Link Analysis
  • Blockchain Technology
  • Information Visualization

For details on specific projects, please see the links on the right or my publications below.

Short CV

09/2018 - present Doctoral Researcher at the Chair of Media Technology at the University of Wuppertal

03/2015 - 08/2018 Doctoral Researcher at the Information Science Group at the University of Konstanz

03/2014 - 02/2015 Visiting Researcher at the National Institute of Informatics Tokyo, Japan 

08/2011 - 02/2014 Visiting Researcher at the University of California, Berkeley, US

Teaching and projects 

I very much enjoy collaborating with other researchers and students. If your are interested in my research, please do not hesitate to contact me. If you are a student looking for a bachelor's or master's project or thesis, please see the various topics I offer related to all areas of my research at our students corner.


Selected Publications

A complete list of my publications is available here.

  • N. Meuschke, V. Stange, M. Schubotz, and B. Gipp, “HyPlag: A Hybrid Approach to Academic Plagiarism Detection,” in Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2018. (PDF)
  • N. Meuschke, C. Gondeck, D. Seebacher, C. Breitinger, D. Keim, and B. Gipp, “An Adaptive Image-based Plagiarism Detection Approach,” in Proceedings of the ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL), Fort Worth, USA, 2018. (PDF) 
  • N. Meuschke, M. Schubotz, F. Hamborg, T. Skopal, and B. Gipp, “Analyzing Mathematical Content to Detect Academic Plagiarism,” in Proceedings of the International Conference on Information and Knowledge Management (CIKM), Singapore, 2017. (PDF)
  • N. Meuschke, N. Siebeck, M. Schubotz, B. Gipp, “Analyzing Semantic Concept Patterns to Detect Academic Plagiarism,” in Proceedings of the 6th International Workshop on Mining Scientific Publications (WOSP) held in conjunction with the ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL), 2017. (PDF) 
  • N. Meuschke and B. Gipp, “State of the Art in Detecting Academic Plagiarism”, International Journal for Educational Integrity, vol. 9, iss. 1, pp. 50-71, 2013. (PDF)
zuletzt bearbeitet am: 28.11.2018