| External and intrinsic plagiarism detection using vector space models M Zechner, M Muhr, R Kern, M Granitzer Proc. SEPLN 32, 47-55, 2009 | 118 | 2009 |
| 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 | 99 | 2010 |
| 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 | 88 | 2021 |
| 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 | 86 | 2010 |
| 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 | 65 | 2022 |
| 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 | 65 | 2012 |
| 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 | 57 | 2021 |
| 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 | 55 | 2010 |
| 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 | 54 | 2012 |
| PySpark and RDKit: moving towards big data in cheminformatics M Lovrić, JM Molero, R Kern Molecular informatics 38 (6), 1800082, 2019 | 53 | 2019 |
| Aspects of broad folksonomies M Lux, M Granitzer, R Kern 18th International Workshop on Database and Expert Systems Applications …, 2007 | 53 | 2007 |
| Authorship identification of documents with high content similarity A Rexha, M Kröll, H Ziak, R Kern Scientometrics, 2018 | 52 | 2018 |
| 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 | 51 | 2023 |
| Teambeam-meta-data extraction from scientific literature R Kern, K Jack, M Hristakeva, M Granitzer D-Lib Magazine 18 (7), 1, 2012 | 46 | 2012 |
| 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 | 43 | 2014 |
| PySpark and RDKit: moving towards big data in cheminformatics M Lovric, R Kern, J Molero Molecular informatics 38 (6), 1800082, 2019 | 42 | 2019 |
| 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 | 41 | 2017 |
| 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 | 41 | 2016 |
| 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 | 39 | 2021 |
| A Literature Survey of Early Time Series Classification and Deep Learning. T Santos, R Kern Sami@ iknow, 2016 | 38 | 2016 |
