Rolf Jagerman
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Data Stream Mining Techniques
- Semantic Web and Ontologies
- Information Systems top 10%
- Recommender Systems and Techniques
- Information Retrieval and Search Behavior
Papers in
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- Topic Modeling 8
- Natural Language Processing Techniques 4
- Domain Adaptation and Few-Shot Learning 4
- Machine Learning and Algorithms 3
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- Recommender Systems and Techniques 3
- Information Retrieval and Search Behavior 2
- Co-authors
- Maarten de Rijke (5 shared papers)Xuanhui Wang (10 shared papers)Michael Bendersky (11 shared papers)Honglei Zhuang (6 shared papers)Zhen Qin (6 shared papers)Ilya Markov (1 shared paper)Kai Hui (3 shared papers)Le Yan (2 shared papers)
- Journals
- Journal of Data and Information Quality (1 paper)Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (1 paper)Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (1 paper)Data Archiving and Networked Services (DANS) (1 paper)UvA-DARE (University of Amsterdam) (2 papers)
- Partner nations
- United StatesNetherlandsNorway
In The Last Decade
Rolf Jagerman
14 papers receiving 150 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 101
- Information Systems 69
- Management Science and Operations Research 32
- Computer Vision and Pattern Recognition 25
- Marketing 10
Countries citing papers authored by Rolf Jagerman
This map shows the geographic impact of Rolf Jagerman'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 Rolf Jagerman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rolf Jagerman more than expected).
Fields of papers citing papers by Rolf Jagerman
This network shows the impact of papers produced by Rolf Jagerman. 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 Rolf Jagerman. The network helps show where Rolf Jagerman may publish in the future.
Co-authors
The 25 scholars most cited alongside Rolf Jagerman, 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 | 2024 | 51 | |
| 2 | 2023 | 29 | |
| 3 | 2019 | 28 | |
| 4 | 2018 | 12 | |
| 5 | 2017 | 8 | |
| 6 | 2019 | 6 | |
| 7 | 2021 | 5 | |
| 8 | 2023 | 4 | |
| 9 | 2022 | 4 | |
| 10 | 2022 | 3 | |
| 11 | 2024 | 2 | |
| 12 | 2024 | 1 | |
| 13 | 2024 | 1 | |
| 14 | Modeling Label Ambiguity for List-Wise Neural Learning to Rank | 2017 | 1 |
| 15 | 2021 | 0 |
About Rolf Jagerman
Rolf Jagerman is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Management Science and Operations Research and Computer Science Applications, having authored 15 papers that have together received 155 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Recommender Systems and Techniques (3 papers), Machine Learning and Algorithms (3 papers), Information Retrieval and Search Behavior (2 papers), Data Quality and Management (2 papers) and Mobile Crowdsensing and Crowdsourcing (2 papers). The work is most often cited by research in Artificial Intelligence (101 citations), Information Systems (69 citations), Management Science and Operations Research (32 citations), Computer Vision and Pattern Recognition (25 citations) and Marketing (10 citations). Rolf Jagerman has collaborated with scholars based in United States, Netherlands and Norway. Frequent co-authors include Maarten de Rijke, Xuanhui Wang, Michael Bendersky, Honglei Zhuang, Zhen Qin, Ilya Markov, Kai Hui, Le Yan, Donald Metzler and Junru Wu. Their work appears in journals such as Journal of Data and Information Quality, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Data Archiving and Networked Services (DANS) and UvA-DARE (University of Amsterdam).
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.