Peer Kröger
Impact in
- Artificial Intelligence top 0.2%
- Advanced Clustering Algorithms Research
- Anomaly Detection Techniques and Applications
- Signal Processing top 0.5%
- Data Management and Algorithms
- Time Series Analysis and Forecasting
Papers in
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- Data Management and Algorithms 44
- Time Series Analysis and Forecasting 13
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- Advanced Clustering Algorithms Research 48
- Anomaly Detection Techniques and Applications 9
- Co-authors
- Hans‐Peter Kriegel (73 shared papers)Arthur Zimek (31 shared papers)Erich Schubert (11 shared papers)Jörg Sander (5 shared papers)Karin Kailing (5 shared papers)Christian Böhm (15 shared papers)Matthias Renz (47 shared papers)Elke Achtert (13 shared papers)
In The Last Decade
Peer Kröger
141 papers receiving 5.2k citations
Peer Kröger's Hit Papers
Peers
Comparison fields: 5 of 140
- Artificial Intelligence 3.1k
- Signal Processing 718
- Computer Vision and Pattern Recognition 505
- Information Systems 478
- Computer Networks and Communications 259
Countries citing papers authored by Peer Kröger
This map shows the geographic impact of Peer Kröger'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 Peer Kröger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peer Kröger more than expected).
Fields of papers citing papers by Peer Kröger
This network shows the impact of papers produced by Peer Kröger. 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 Peer Kröger. The network helps show where Peer Kröger may publish in the future.
Co-authors
The 25 scholars most cited alongside Peer Kröger, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 161 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Clustering high-dimensional data Hit paper breakdown → | 2009 | 887 |
| 2 | Density‐based clustering Hit paper breakdown → | 2011 | 656 |
| 3 | LoOP Hit paper breakdown → | 2009 | 385 |
| 4 | 2004 | 280 | |
| 5 | 2009 | 240 | |
| 6 | 2011 | 207 | |
| 7 | 2010 | 201 | |
| 8 | 2007 | 129 | |
| 9 | 2005 | 120 | |
| 10 | 2004 | 115 | |
| 11 | 2006 | 109 | |
| 12 | 2006 | 102 | |
| 13 | 2012 | 92 | |
| 14 | 2012 | 88 | |
| 15 | 2019 | 85 | |
| 16 | On Using Class-Labels in Evaluation of Clusterings | 2010 | 83 |
| 17 | 2008 | 71 | |
| 18 | 2001 | 60 | |
| 19 | 2006 | 60 | |
| 20 | 2003 | 58 |
About Peer Kröger
Peer Kröger is a scholar working on Signal Processing, Artificial Intelligence, Paleontology, Information Systems and Management and Information Systems, having authored 161 papers that have together received 5.5k indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (48 papers), Data Management and Algorithms (44 papers), Archaeology and ancient environmental studies (15 papers), Time Series Analysis and Forecasting (13 papers), Anomaly Detection Techniques and Applications (9 papers), Scientific Computing and Data Management (8 papers), Advanced Database Systems and Queries (6 papers) and Research Data Management Practices (5 papers). The work is most often cited by research in Artificial Intelligence (3.1k citations), Signal Processing (718 citations), Computer Vision and Pattern Recognition (505 citations), Information Systems (478 citations) and Computer Networks and Communications (259 citations). Peer Kröger has collaborated with scholars based in Germany, Canada and Japan. Frequent co-authors include Hans‐Peter Kriegel, Arthur Zimek, Erich Schubert, Jörg Sander, Karin Kailing, Christian Böhm, Matthias Renz, Elke Achtert, H.-P. Kriegel and Alexey Pryakhin. Their work appears in journals such as Lecture notes in computer science, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, Rapid Communications in Mass Spectrometry, Distributed and Parallel Databases and Data Mining and Knowledge Discovery.
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.