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Dr. Norman Meuschke2022-07-15T19:28:29+02:00

Dr. Norman Meuschke

Senior Researcher for Information Retrieval

Office: SUB Historic Building 0.211


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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 (esp. for text, images, and mathematical content)
  • Natural Language Processing
  • 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.

Teaching & Projects

I very much enjoy collaborating with other researchers and students. If you 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.


Dr. Norman Meuschke

Papendiek 14
37073 Göttingen

Office: SUB Historic Building 0.211
Mail: meuschke@uni-goettingen.de
Phone: +49 551 39 25833
Schedule an appointment

Project websites

Social Network Profiles

Short CV

05/2022 – present

Scientific Information Analytics Group, University of Göttingen

09/2018 – 04/2022

Data & Knowledge Engineering Group, University of Wuppertal

03/2015 – 08/2018

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

Doctoral Thesis

Analyzing Non-Textual Content Elements to Detect Academic Plagiarism, University of Konstanz, 2021, Grade: summa cum laude (excellent).

PDF | DOI | BibTeX

Resources for my thesis
(Data and source code, recording and slides of my doctoral defense)

Selected Publications

All Publications   |   Google Scholar Profile

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.
(PDF  DOI  BibTeX)

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  BibTeX  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.
(PDF  DOI  BibTeX)

Media Coverage

Newspaper FAZ reports on our research to detect and deter academic plagiarism

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 misconduct. Click on the image above for accessing a zoomable version of the complete article.

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