Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Stefan Wrobel's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stefan Wrobel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Wrobel more than expected).
This network shows the impact of papers produced by Stefan Wrobel. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stefan Wrobel. The network helps show where Stefan Wrobel may publish in the future.
Co-authorship network of co-authors of Stefan Wrobel
This figure shows the co-authorship network connecting the top 25 collaborators of Stefan Wrobel.
A scholar is included among the top collaborators of Stefan Wrobel based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Stefan Wrobel. Stefan Wrobel is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Bauckhage, Christian, Nico Piatkowski, Rafet Sifa, Dirk Hecker, & Stefan Wrobel. (2019). A QUBO Formulation of the k-Medoids Problem.. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 54–63.9 indexed citations
6.
Bauckhage, Christian, et al.. (2018). Informed Machine Learning Through Functional Composition.. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 33–37.4 indexed citations
7.
Bauckhage, Christian, et al.. (2018). Adiabatic Quantum Computing for Kernel k=2 Means Clustering.. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 21–32.6 indexed citations
Rüping, Stefan, et al.. (2009). Metadata Extraction using Text Mining. Studies in health technology and informatics. 147. 95–104.1 indexed citations
10.
Raedt, Luc De & Stefan Wrobel. (2005). Proceedings, Twenty-Second International Conference on Machine Learning.22 indexed citations
11.
Wrobel, Stefan, et al.. (2003). Learning Minesweeper with multirelational learning. International Joint Conference on Artificial Intelligence. 533–538.6 indexed citations
Scheffer, Tobias, et al.. (2002). Lerning Hidden Markov Models for Information Extraction Actively from Partially Labeled Text.. Künstliche Intell.. 16. 17–22.5 indexed citations
14.
Raedt, Luc De, David Page, & Stefan Wrobel. (2001). Special issue on inductive logic programming. Machine Learning. 43. 5–6.2 indexed citations
15.
Wrobel, Stefan. (2001). Inductive logic programming for knowedge discovery in databases. Springer eBooks. 74–99.1 indexed citations
16.
Scheffer, Tobias & Stefan Wrobel. (2001). Incremental Maximization of Non-Instance-Averaging Utility Functions with Applications to Knowledge Discovery Problems. International Conference on Machine Learning. 481–488.3 indexed citations
17.
Horváth, Tamás, et al.. (1998). Measuring similarity of RNA structures by relational instance-based learning: A first step toward detecting RNA signal structures in silico..1 indexed citations
18.
Wrobel, Stefan. (1998). Data Mining und Wissensentdeckung in Datenbanken.. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 12. 6–10.2 indexed citations
Wrobel, Stefan. (1990). Design goals for sloppy modeling systems. OpenGrey (Institut de l'Information Scientifique et Technique). 357–373.3 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.