Robert Görke
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Artificial Intelligence top 5%
- Advanced Clustering Algorithms Research
- Advanced Graph Neural Networks
Papers in
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- Complex Network Analysis Techniques 10
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- Advanced Clustering Algorithms Research 9
- Advanced Graph Neural Networks 3
- Co-authors
- Dorothea Wagner (9 shared papers)Marco Gaertler (5 shared papers)Daniel Delling (3 shared papers)Ulrik Brandes (2 shared papers)Martin Hoefer (2 shared papers)Zoran Nikoloski (2 shared papers)Alexander Wolff (2 shared papers)Mark R. Emmett (2 shared papers)
- Journals
- Journal of Graph Algorithms and Applications (2 papers)BMC Systems Biology (1 paper)Networks and Heterogeneous Media (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)ACM Journal of Experimental Algorithmics (2 papers)
- Partner nations
- GermanyUnited StatesCzechia
In The Last Decade
Robert Görke
14 papers receiving 846 citations
Robert Görke's Hit Papers
Peers
Comparison fields: 5 of 134
- Statistical and Nonlinear Physics 531
- Artificial Intelligence 267
- Computer Networks and Communications 144
- Transportation 36
- Computational Theory and Mathematics 65
Countries citing papers authored by Robert Görke
This map shows the geographic impact of Robert Görke'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 Robert Görke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Görke more than expected).
Fields of papers citing papers by Robert Görke
This network shows the impact of papers produced by Robert Görke. 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 Robert Görke. The network helps show where Robert Görke may publish in the future.
Co-authors
The 19 scholars most cited alongside Robert Görke, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | On Modularity Clustering Hit paper breakdown → | 2008 | 749 |
| 2 | 2006 | 43 | |
| 3 | 2010 | 24 | |
| 4 | 2013 | 19 | |
| 5 | 2008 | 9 | |
| 6 | 2007 | 8 | |
| 7 | 2008 | 6 | |
| 8 | 2012 | 6 | |
| 9 | 2012 | 3 | |
| 10 | Constructing the city Voronoi diagram faster. | 2005 | 3 |
| 11 | 2014 | 2 | |
| 12 | 2010 | 2 | |
| 13 | 2011 | 1 | |
| 14 | 2009 | 1 |
About Robert Görke
Robert Görke is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Signal Processing, Computer Networks and Communications and Molecular Biology, having authored 14 papers that have together received 876 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Advanced Clustering Algorithms Research (9 papers), Data Management and Algorithms (4 papers), Advanced Graph Neural Networks (3 papers), Metabolomics and Mass Spectrometry Studies (1 paper), Graph theory and applications (1 paper), Gene expression and cancer classification (1 paper) and Data Visualization and Analytics (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (531 citations), Artificial Intelligence (267 citations), Computer Networks and Communications (144 citations), Transportation (36 citations) and Computational Theory and Mathematics (65 citations). Robert Görke has collaborated with scholars based in Germany, United States and Czechia. Frequent co-authors include Dorothea Wagner, Marco Gaertler, Daniel Delling, Ulrik Brandes, Martin Hoefer, Zoran Nikoloski, Alexander Wolff, Mark R. Emmett, Charles A. Conrad and Christian Staudt. Their work appears in journals such as Journal of Graph Algorithms and Applications, BMC Systems Biology, Networks and Heterogeneous Media, IEEE Transactions on Knowledge and Data Engineering and ACM Journal of Experimental Algorithmics.
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.