Benjamin Hilprecht
Impact in
- Signal Processing top 5%
- Data Management and Algorithms
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- Advanced Database Systems and Queries
Papers in
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- Data Stream Mining Techniques 5
- Machine Learning and Data Classification 2
- Privacy-Preserving Technologies in Data 1
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- Advanced Database Systems and Queries 3
- Advanced Data Storage Technologies 1
- Co-authors
- Carsten Binnig (6 shared papers)Andreas Schmidt (2 shared papers)Alejandro Molina (1 shared paper)Kristian Kersting (1 shared paper)Uwe Röhm (3 shared papers)Tobias Ziegler (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (2 papers)SHILAP Revista de lepidopterología (1 paper)TUbilio (Technical University of Darmstadt) (3 papers)
- Partner nations
- GermanyAustraliaUnited States
In The Last Decade
Benjamin Hilprecht
7 papers receiving 295 citations
Peers
Comparison fields: 5 of 34
- Signal Processing 129
- Computer Networks and Communications 152
- Artificial Intelligence 199
- Health Informatics 4
- Computer Vision and Pattern Recognition 55
Countries citing papers authored by Benjamin Hilprecht
This map shows the geographic impact of Benjamin Hilprecht'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 Benjamin Hilprecht with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Hilprecht more than expected).
Fields of papers citing papers by Benjamin Hilprecht
This network shows the impact of papers produced by Benjamin Hilprecht. 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 Benjamin Hilprecht. The network helps show where Benjamin Hilprecht may publish in the future.
Co-authors
The 6 scholars most cited alongside Benjamin Hilprecht, 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 | 2020 | 122 | |
| 2 | 2019 | 89 | |
| 3 | 2020 | 42 | |
| 4 | 2022 | 30 | |
| 5 | 2019 | 13 | |
| 6 | 2023 | 4 | |
| 7 | DBMS Fitting: Why should we learn what we already know? | 2020 | 1 |
About Benjamin Hilprecht
Benjamin Hilprecht is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Information Systems and Computer Vision and Pattern Recognition, having authored 7 papers that have together received 301 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (5 papers), Advanced Database Systems and Queries (3 papers), Machine Learning and Data Classification (2 papers), Privacy-Preserving Technologies in Data (1 paper), Time Series Analysis and Forecasting (1 paper), Advanced Data Storage Technologies (1 paper), Parallel Computing and Optimization Techniques (1 paper) and Scientific Computing and Data Management (1 paper). The work is most often cited by research in Signal Processing (129 citations), Computer Networks and Communications (152 citations), Artificial Intelligence (199 citations), Health Informatics (4 citations) and Computer Vision and Pattern Recognition (55 citations). Benjamin Hilprecht has collaborated with scholars based in Germany, Australia and United States. Frequent co-authors include Carsten Binnig, Andreas Schmidt, Alejandro Molina, Kristian Kersting, Uwe Röhm and Tobias Ziegler. Their work appears in journals such as Proceedings of the VLDB Endowment, SHILAP Revista de lepidopterología and TUbilio (Technical University of Darmstadt).
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.