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Roman Kern
Roman Kern
Know Center, Graz University of Technology
Verified email at know-center.at - Homepage
Title
Cited by
Cited by
Year
External and intrinsic plagiarism detection using vector space models
M Zechner, M Muhr, R Kern, M Granitzer
Proc. SEPLN 32, 47-55, 2009
1172009
Why do users tag? Detecting users’ motivation for tagging in social tagging systems
M Strohmaier, C Körner, R Kern
Proceedings of the International AAAI Conference on Web and Social Media 4 …, 2010
992010
Of categorizers and describers: An evaluation of quantitative measures for tagging motivation
C Körner, R Kern, HP Grahsl, M Strohmaier
Proceedings of the 21st ACM conference on Hypertext and hypermedia, 157-166, 2010
862010
Understanding the true effects of the COVID-19 lockdown on air pollution by means of machine learning
M Lovrić, K Pavlović, M Vuković, SK Grange, M Haberl, R Kern
Environmental pollution 274, 115900, 2021
842021
Understanding why users tag: A survey of tagging motivation literature and results from an empirical study
M Strohmaier, C Körner, R Kern
Journal of Web Semantics 17, 1-11, 2012
652012
Machine learning in continuous casting of steel: A state-of-the-art survey
D Cemernek, S Cemernek, H Gursch, A Pandeshwar, T Leitner, M Berger, ...
Journal of Intelligent Manufacturing, 1-19, 2022
552022
External and intrinsic plagiarism detection using a cross-lingual retrieval and segmentation system
M Muhr, R Kern, M Zechner, M Granitzer
Notebook papers of CLEF 2010 LABs and workshops, 22, 2010
552010
Evaluation of folksonomy induction algorithms
M Strohmaier, D Helic, D Benz, C Körner, R Kern
ACM Transactions on Intelligent Systems and Technology (TIST) 3 (4), 1-22, 2012
542012
Aspects of broad folksonomies
M Lux, M Granitzer, R Kern
18th International Workshop on Database and Expert Systems Applications …, 2007
532007
Authorship identification of documents with high content similarity
A Rexha, M Kröll, H Ziak, R Kern
Scientometrics, 2018
512018
Machine learning in prediction of intrinsic aqueous solubility of drug‐like compounds: Generalization, complexity, or predictive ability?
M Lovrić, K Pavlović, P Žuvela, A Spataru, B Lučić, R Kern, MW Wong
Journal of chemometrics 35 (7-8), e3349, 2021
502021
PySpark and RDKit: moving towards big data in cheminformatics
M Lovrić, JM Molero, R Kern
Molecular informatics 38 (6), 1800082, 2019
482019
Teambeam-meta-data extraction from scientific literature
R Kern, K Jack, M Hristakeva, M Granitzer
D-Lib Magazine 18 (7), 1, 2012
462012
Unsupervised document structure analysis of digital scientific articles
S Klampfl, M Granitzer, K Jack, R Kern
International journal on digital libraries 14, 83-99, 2014
432014
How to keep text private? A systematic review of deep learning methods for privacy-preserving natural language processing
S Sousa, R Kern
Artificial Intelligence Review 56 (2), 1427-1492, 2023
412023
Polarity classification for target phrases in tweets: a Word2Vec approach
A Rexha, M Kröll, M Dragoni, R Kern
European Semantic Web Conference, 217-223, 2016
412016
Big data as a promoter of industry 4.0: Lessons of the semiconductor industry
D Cemernek, H Gursch, R Kern
2017 IEEE 15th International Conference on Industrial Informatics (INDIN …, 2017
402017
PySpark and RDKit: moving towards big data in cheminformatics
M Lovric, R Kern, J Molero
Molecular informatics 38 (6), 1800082, 2019
392019
Deep learning—a first meta-survey of selected reviews across scientific disciplines, their commonalities, challenges and research impact
J Egger, A Pepe, C Gsaxner, Y Jin, J Li, R Kern
PeerJ Computer Science 7, e773, 2021
382021
A Literature Survey of Early Time Series Classification and Deep Learning.
T Santos, R Kern
Sami@ iknow, 2016
382016
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