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Data Science

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Beteiligte Personen
Dr. Michael Färber
Dr.-Ing. Tobias Käfer
Prof. Dr. Sanja Lazarova-Molnar
M.Sc. Ebrahim Norouzi
M.Sc. Nicholas Popovic
M.Sc. Zhan Qu
M.Sc. Fabian Rybinski
Prof. Dr. York Sure-Vetter
M.Sc. Angew. Inf. Meike Ullrich


Lehrveranstaltungen
TypSemesterNameLink
SeminarSSData Science & Real-Time Big Data Analytics
SeminarSSGraph Representation Learning
SeminarSSKnowledge Discovery and Data Mining
VorlesungWSAnwendungen der KI
VorlesungWSKnowledge Discovery
VorlesungSSSemantic Web Technologies


Aktive Projekte


Veröffentlichungen zum Forschungsgebiet

Article
Michael Färber, Jannik Schwade, Adam Jatowt
Measuring Variety, Balance, and Disparity: An Analysis of Media Coverage of the 2021 German Federal Election
arXiv, 2023
(Details)


Michael Färber, Lin Ao
The Microsoft Academic Knowledge Graph Enhanced: Author Name Disambiguation, Publication Classification, and Embeddings
Quantitative Science Studies, Februar, 2022
(Details)


Konstantin D. Pandl, Scott Thiebes, Manuel Schmidt-Kraepelin, Ali Sunyaev
How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19
Scientific Reports, 11, (1), Seiten 9414, Mai, 2021
(Details)


Michael Färber, Carsten Menne, Andreas Harth
A Linked Data Wrapper for CrunchBase
Semantic Web Journal, 9, (4), Seiten 505–5015, 2018
(Details)


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inproceedings
Konstantin D. Pandl, Fabian Feiland, Scott Thiebes, Ali Sunyaev
Trustworthy machine learning for health care: scalable data valuation with the shapley value
Proceedings of the Conference on Health, Inference, and Learning, Seiten: 47–57, Association for Computing Machinery (ACM), April, 2021
(Details)


Michael Färber, Victoria Burkard, Adam Jatowt, Lim Sora
A Multidimensional Dataset Based on Crowdsourcing for Analyzing and Detecting News Bias
Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM'20), ACM, Galway, Ireland
(Details)


Michael Färber
Analyzing the GitHub Repositories of Research Papers
Proceedings of the 20th ACM/IEEE Joint Conference on Digital Libraries (JCDL'20), ACM, Xi'an, China
(Details)


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