Johann Petrak
- Artificial Intelligence top 5%
- Information Systems top 10%
- Sociology and Political Science
- Management Science and Operations Research
- Computer Vision and Pattern Recognition
- Co-authors
- Diana MaynardKalina BontchevaJohannes FürnkranzLeon DerczynskiRaphaël TroncyGiuseppe RizzoMarieke van ErpGenevieve Gorrell
- Topics
- Topic Modeling (5 papers)Natural Language Processing Techniques (5 papers)Data Mining Algorithms and Applications (3 papers)
- Partner nations
- United KingdomAustriaFrance
In The Last Decade
Johann Petrak
15 papers receiving 363 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 311
- Information Systems 92
- Sociology and Political Science 67
- Management Science and Operations Research 28
- Computer Vision and Pattern Recognition 27
Countries citing papers authored by Johann Petrak
This map shows the geographic impact of Johann Petrak'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 Johann Petrak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johann Petrak more than expected).
Fields of papers citing papers by Johann Petrak
This network shows the impact of papers produced by Johann Petrak. 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 Johann Petrak. The network helps show where Johann Petrak may publish in the future.
Co-authorship network of co-authors of Johann Petrak
This figure shows the co-authorship network connecting the top 25 collaborators of Johann Petrak. A scholar is included among the top collaborators of Johann Petrak 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 Johann Petrak. Johann Petrak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 37 | |
| 2 | 4 | |
| 3 | 28 | |
| 4 | 13 | |
| 5 | 20 | |
| 6 | 3 | |
| 7 | 207 | |
| 8 | On the Use of Fast Subsampling Estimates for Algorithm Recommendation | 4 |
| 9 | Hybrid Decision Tree Learners with Alternative Leaf Classifiers: An Empirical Study | 11 |
| 10 | An Evaluation of Landmarking Variants | 41 |
| 11 | 13 | |
| 12 | Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases | 7 |
| 13 | Machine Learning Methods for International Conflict Databases: A Case Study in Predicting Mediation Outcome | 2 |
| 14 | The Potential Contribution of AI to the Avoidance of Crises and Wars: Using CBR Methods with the KOSIMO Database of Conflicts | 2 |
| 15 | 3 |
About Johann Petrak
Johann Petrak is a scholar working on Artificial Intelligence, General Social Sciences and Communication, having authored 15 papers that have together received 395 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers) and Data Mining Algorithms and Applications (3 papers). The work is most often cited by research in Artificial Intelligence (311 citations), Information Systems (92 citations) and General Social Sciences (13 citations). Johann Petrak has collaborated with scholars based in United Kingdom, Austria and France. Frequent co-authors include Diana Maynard, Kalina Bontcheva, Johannes Fürnkranz, Leon Derczynski, Raphaël Troncy, Giuseppe Rizzo, Marieke van Erp, Genevieve Gorrell, Xingyi Song and Ye Jiang. Their work appears in journals such as PLoS ONE, Scientometrics and Information Processing & Management.
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.