Peter Prettenhofer
- Artificial Intelligence top 5%
- Topic Modeling 5
- Text and Document Classification Technologies 2
- Sentiment Analysis and Opinion Mining 1
- Authorship Attribution and Profiling 1
- Safety Research top 10%
- Academic integrity and plagiarism 1
- Information Systems top 10%
- Information Retrieval and Search Behavior 1
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- Digital Marketing and Social Media 1
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- Computational Drug Discovery Methods 1
- Co-authors
- Benno SteinNedim LipkaGilles LouppeMarkus StrohmaierMathias LuxHenning WachsmuthMark Kröll
- Journals
- Language Resources and Evaluation (1 paper)ACM Transactions on Intelligent Systems and Technology (1 paper)International Conference on Computational Linguistics (1 paper)
In The Last Decade
Peter Prettenhofer
8 papers receiving 337 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 298
- Safety Research 32
- Information Systems 46
- Computer Vision and Pattern Recognition 38
- Computational Mathematics 1
Countries citing papers authored by Peter Prettenhofer
This map shows the geographic impact of Peter Prettenhofer'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 Peter Prettenhofer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Prettenhofer more than expected).
Fields of papers citing papers by Peter Prettenhofer
This network shows the impact of papers produced by Peter Prettenhofer. 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 Peter Prettenhofer. The network helps show where Peter Prettenhofer may publish in the future.
Co-authorship network
The 7 scholars most cited alongside Peter Prettenhofer, 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 | 2014 | 48 | |
| 2 | Forecasting Daily Solar Energy Production Using Robust Regression Techniques | 2014 | 1 |
| 3 | 2011 | 40 | |
| 4 | Cross-Language Text Classification Using Structural Correspondence Learning | 2010 | 170 |
| 5 | Efficient Statement Identification for Automatic Market Forecasting | 2010 | 6 |
| 6 | 2010 | 91 | |
| 7 | Different degrees of explicitness in intentional artifacts: studying user goals in a large search query log | 2008 | 5 |
| 8 | 2008 | 4 |
About Peter Prettenhofer
Peter Prettenhofer is a scholar working on Artificial Intelligence, Safety Research, Marketing, Signal Processing and Statistical and Nonlinear Physics, having authored 8 papers that have together received 365 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Text and Document Classification Technologies (2 papers), Information Retrieval and Search Behavior (1 paper), Academic integrity and plagiarism (1 paper), Sentiment Analysis and Opinion Mining (1 paper), Digital Marketing and Social Media (1 paper), Computational Drug Discovery Methods (1 paper) and Authorship Attribution and Profiling (1 paper). The work is most often cited by research in Artificial Intelligence (298 citations), Safety Research (32 citations), Information Systems (46 citations), Computer Vision and Pattern Recognition (38 citations) and Computational Mathematics (1 citation). Peter Prettenhofer has collaborated with scholars based in Germany, Austria and Belgium. Frequent co-authors include Benno Stein, Nedim Lipka, Gilles Louppe, Markus Strohmaier, Mathias Lux, Henning Wachsmuth and Mark Kröll. Their work appears in journals such as Language Resources and Evaluation, ACM Transactions on Intelligent Systems and Technology, International Conference on Computational Linguistics, Meeting of the Association for Computational Linguistics and Open Repository and Bibliography (University of Liège).
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.