Contact
Dr. 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
Social network profiles
Dr. Norman Meuschke
Senior Researcher for Information Retrieval
Office: FC 1.20
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.
SHORT CV
| 09/2018 - present | Researcher Data & Knowledge Engineering Group, University of Wuppertal |
| 03/2015 - 08/2018 | 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 |
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.
[WS21]
Programming in Python - extended
Key Competences in Computer Science
Seminar Selected Topics in Data & Knowledge Engineering
Practical Project Information Technology
[SS21]
SELECTED PUBLICATIONS
A complete list of my publications is available here.
| Doctoral Thesis Analyzing Non-Textual Content Elements to Detect Academic Plagiarism N. Meuschke University of Konstanz, 2021. (PDF DOI BibTeX Data, Code, Resources) |
| 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
zuletzt bearbeitet am: 28.11.2021