Christian Borgelt
- Signal Processing top 1%
- Data Management and Algorithms 12
- Information Systems top 0.5%
- Data Mining Algorithms and Applications 24
- Artificial Intelligence top 1%
- Bayesian Modeling and Causal Inference 14
- Neural Networks and Applications 10
- Advanced Clustering Algorithms Research 9
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- Rough Sets and Fuzzy Logic 16
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- Neural dynamics and brain function 12
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- Multi-Criteria Decision Making 8
Christian Borgelt
90 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 174
- Signal Processing 459
- Information Systems 859
- Artificial Intelligence 1.1k
- Computational Theory and Mathematics 552
- Computer Vision and Pattern Recognition 392
Countries citing papers authored by Christian Borgelt
This map shows the geographic impact of Christian Borgelt'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 Christian Borgelt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christian Borgelt more than expected).
Fields of papers citing papers by Christian Borgelt
This network shows the impact of papers produced by Christian Borgelt. 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 Christian Borgelt. The network helps show where Christian Borgelt may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Christian Borgelt, 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 | 2023 | 2 | |
| 2 | 2020 | 12 | |
| 3 | 2017 | 29 | |
| 4 | 2016 | 6 | |
| 5 | 2013 | 48 | |
| 6 | 2013 | 20 | |
| 7 | 2009 | 10 | |
| 8 | Support Computation for Mining Frequent Subgraphs in a Single Graph. | 2007 | 40 |
| 9 | From Data and Information Analysis to Knowledge Engineering: Proceedings of the 29th Annual Conference of the Gesellschaft für Klassifikation e.V., University ... Data Analysis, and Knowledge Organization) | 2006 | 1 |
| 10 | 2005 | 6 | |
| 11 | 2004 | 3 | |
| 12 | Recursion Pruning for the Apriori Algorithm. | 2004 | 27 |
| 13 | Fast Fuzzy Clustering of Web Page Collections | 2004 | 14 |
| 14 | Dependence relationships between Gene Ontology terms based on TIGR gene product annotations | 2004 | 35 |
| 15 | 2003 | 2 | |
| 16 | 2003 | 4 | |
| 17 | 2003 | 9 | |
| 18 | 2000 | 13 | |
| 19 | Lernen probabilistischer und possibilistischer Netze aus Daten: Theorie und Anwendung. | 1998 | 0 |
| 20 | 1998 | 1 |
About Christian Borgelt
Christian Borgelt is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Signal Processing, having authored 101 papers that have together received 2.4k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (24 papers), Rough Sets and Fuzzy Logic (16 papers), Bayesian Modeling and Causal Inference (14 papers), Data Management and Algorithms (12 papers), Neural dynamics and brain function (12 papers), Neural Networks and Applications (10 papers), Advanced Clustering Algorithms Research (9 papers) and Multi-Criteria Decision Making (8 papers). The work is most often cited by research in Signal Processing (459 citations), Information Systems (859 citations) and Artificial Intelligence (1.1k citations). Christian Borgelt has collaborated with scholars based in Germany, Spain and Japan. Frequent co-authors include Michael R. Berthold, Rudolf Kruse, Frank Klawonn, Matthias Steinbrecher, Christian Döring, Heiko Timm, Christian Braune, Sanaz Mostaghim, Christian Moewes and Sonja Grün. Their work appears in journals such as Scientific Reports, Information Sciences and Epilepsia.
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.