Michael Wurst
Impact in
- Signal Processing top 5%
- Music and Audio Processing
- Artificial Intelligence top 5%
- Data Stream Mining Techniques
- Semantic Web and Ontologies
- Machine Learning and Data Classification
Papers in
-
- Data Stream Mining Techniques 6
- Advanced Clustering Algorithms Research 4
- Metaheuristic Optimization Algorithms Research 4
- Semantic Web and Ontologies 4
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- Recommender Systems and Techniques 7
- Data Mining Algorithms and Applications 3
- Co-authors
- Ingo Mierswa (8 shared papers)Martin Scholz (2 shared papers)Ralf Klinkenberg (1 shared paper)Katharina Morik (7 shared papers)Jasminko Novak (4 shared papers)Geoffrey D. Hannigan (1 shared paper)Christopher H. Woelk (1 shared paper)Gergely Temesi (1 shared paper)
- Journals
- Lecture notes in computer science (10 papers)Future Generation Computer Systems (1 paper)Nucleic Acids Research (1 paper)Knowledge and Information Systems (1 paper)PLoS ONE (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Michael Wurst
25 papers receiving 1.3k citations
Michael Wurst's Hit Papers
Peers
Comparison fields: 5 of 149
- Signal Processing 207
- Artificial Intelligence 552
- Computer Science Applications 86
- Information Systems 281
- Computer Vision and Pattern Recognition 200
Countries citing papers authored by Michael Wurst
This map shows the geographic impact of Michael Wurst'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 Michael Wurst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Wurst more than expected).
Fields of papers citing papers by Michael Wurst
This network shows the impact of papers produced by Michael Wurst. 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 Michael Wurst. The network helps show where Michael Wurst may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Wurst, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | YALE Hit paper breakdown → | 2006 | 826 |
| 2 | 2019 | 231 | |
| 3 | 2005 | 77 | |
| 4 | 2015 | 56 | |
| 5 | 2006 | 42 | |
| 6 | 2005 | 25 | |
| 7 | 2006 | 21 | |
| 8 | 2004 | 21 | |
| 9 | 2014 | 19 | |
| 10 | 2011 | 13 | |
| 11 | 2010 | 11 | |
| 12 | 2005 | 10 | |
| 13 | Mining residential household information from low-resolution smart meter data | 2012 | 9 |
| 14 | 2013 | 8 | |
| 15 | 2006 | 6 | |
| 16 | 2006 | 6 | |
| 17 | Ubiquitous data | 2010 | 6 |
| 18 | 2006 | 5 | |
| 19 | 2020 | 5 | |
| 20 | Sound Multi-objective Feature Space Transformation for Clustering | 2006 | 4 |
About Michael Wurst
Michael Wurst is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications, having authored 30 papers that have together received 1.4k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (7 papers), Data Stream Mining Techniques (6 papers), Data Management and Algorithms (5 papers), Advanced Clustering Algorithms Research (4 papers), Metaheuristic Optimization Algorithms Research (4 papers), Semantic Web and Ontologies (4 papers), Data Mining Algorithms and Applications (3 papers) and Time Series Analysis and Forecasting (3 papers). The work is most often cited by research in Signal Processing (207 citations), Artificial Intelligence (552 citations), Computer Science Applications (86 citations), Information Systems (281 citations) and Computer Vision and Pattern Recognition (200 citations). Michael Wurst has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Ingo Mierswa, Martin Scholz, Ralf Klinkenberg, Katharina Morik, Jasminko Novak, Geoffrey D. Hannigan, Christopher H. Woelk, Gergely Temesi, Rurun Wang and David Příhoda. Their work appears in journals such as Lecture notes in computer science, Future Generation Computer Systems, Nucleic Acids Research, Knowledge and Information Systems and PLoS ONE.
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.