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Norman Meuschke

Data & Knowledge Engineering Group
University of Wuppertal
School of Electrical,
Information and Media Engineering
Rainer-Gruenter-Str. 21
D-42119 Wuppertal
Office: FC 1.20

Phone: +49 (0)202 439 1618


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Norman Meuschke

Doctoral Researcher

Office: FC 1.20


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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.


09/2018 - present Doctoral Researcher
Data & Knowledge Engineering Group, University of Wuppertal
03/2015 - 08/2018 Doctoral Researcher
Information Science Group, University of Konstanz
03/2014 - 02/2015 Visiting Researcher
National Institute of Informatics Tokyo, Japan
08/2011 - 02/2014 Visiting Researcher
University of California, Berkeley, US


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.


Information Retrieval
Seminar Selected Topics in Data Science


Introduction to Computing for Non-Computer Science Majors - lectures and tutorials
Seminar Selected Topics in Media Informatics


A complete list of my publications is available here.

Academic Plagiarism Detection: A Systematic Literature Review
T. Foltynek, N. Meuschke, B. Gipp
ACM Computing Surveys, vol. 52, iss. 6, p. 112:1-112:42, 2019.
Improving Academic Plagiarism Detection for STEM Documents by Analyzing Mathematical Content and Citations
N. Meuschke, V. Stange, M. Schubotz, M. Kramer, B. Gipp
ACM/IEEE-CS Joint Conf. on Digital Libraries (JCDL), 2019.
(PDF  DOI  Slides)
HyPlag: A Hybrid Approach to Academic Plagiarism Detection
N. Meuschke, V. Stange, M. Schubotz, B. Gipp
Proc. Int. ACM SIGIR Conf. on Research and Development in Information Retrieval (SIGIR), 2018
(PDF  DOI  BibTeX)
An Adaptive Image-based Plagiarism Detection Approach
N. Meuschke, C. Gondeck, D. Seebacher, C. Breitinger, D. Keim, B. Gipp
Proc. ACM / IEEE-CS Joint Conf. on Digital Libraries (JCDL), 2018
(PDF  DOI  BibTeX  Slides)
Analyzing Mathematical Content to Detect Academic Plagiarism
N. Meuschke, M. Schubotz, F. Hamborg, T. Skopal, B. Gipp
Proc. ACM Int. Conf. on Information and Knowledge Management (CIKM), 2017.
State of the Art in Detecting Academic Plagiarism
N. Meuschke, B. Gipp
Int. Journal for Educational Integrity, vol. 9, iss. 1, pp. 50-71, 2013.


The Frankfurter Allgemeine Zeitung (FAZ) describes how our research on novel plagiarism detection methods and blockchain-backed decentralized trusted timestamping facilitates combating plagiarism and other forms of academic...


Felix Hamborg and Norman Meuschke received the Best Student Paper Award for their paper Matrix-based News Aggregation: Exploring different News Perspectives; at the A* ranked Joint Conference on Digital Libraries (JCDL)...


The Special Interest Group on Information Retrieval (SIGIR) within the Association for Computing Machinery (ACM) has selected Norman Meuschke as one of ten students to represent SIGIR at the 50th ACM Turing Award Celebration...

zuletzt bearbeitet am: 21.10.2019