Peter Bloem
Impact in
-
- Advanced Graph Neural Networks
- Topic Modeling
- Semantic Web and Ontologies
-
- Data Quality and Management
Papers in
-
- Genomics and Phylogenetic Studies 2
- Biomedical Text Mining and Ontologies 2
- Bioinformatics and Genomic Networks 2
-
- Advanced Graph Neural Networks 3
- Semantic Web and Ontologies 2
- Co-authors
- Victor de Boer (2 shared papers)Steven de Rooij (1 shared paper)Paul Groth (1 shared paper)Gerben Klaas Dirk de Vries (2 shared papers)Jennifer R. Ramautar (1 shared paper)Arthur-Ervin Avrămiea (1 shared paper)Simon J. Houtman (1 shared paper)Klaus Linkenkaer‐Hansen (2 shared papers)
- Journals
- Scientific Reports (1 paper)Frontiers in Neuroinformatics (1 paper)Data Mining and Knowledge Discovery (1 paper)PeerJ Computer Science (1 paper)eNeuro (1 paper)
- Partner nations
- NetherlandsUnited States
In The Last Decade
Peter Bloem
9 papers receiving 80 citations
Peers
Comparison fields: 5 of 41
- Artificial Intelligence 47
- Management Science and Operations Research 12
- Signal Processing 8
- Health Informatics 1
- Geography, Planning and Development 4
Countries citing papers authored by Peter Bloem
This map shows the geographic impact of Peter Bloem'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 Bloem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Bloem more than expected).
Fields of papers citing papers by Peter Bloem
This network shows the impact of papers produced by Peter Bloem. 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 Bloem. The network helps show where Peter Bloem may publish in the future.
Co-authors
The 11 scholars most cited alongside Peter Bloem, 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 | 2017 | 35 | |
| 2 | 2022 | 14 | |
| 3 | 2020 | 9 | |
| 4 | 2022 | 8 | |
| 5 | 2022 | 6 | |
| 6 | Simplifying RDF Data for Graph-Based Machine Learning. | 2014 | 5 |
| 7 | Machine learning on linked data, a position paper | 2014 | 4 |
| 8 | 2023 | 3 | |
| 9 | 2021 | 2 |
About Peter Bloem
Peter Bloem is a scholar working on Molecular Biology, Artificial Intelligence, Statistical and Nonlinear Physics, Cognitive Neuroscience and Management Science and Operations Research, having authored 9 papers that have together received 86 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (3 papers), Complex Network Analysis Techniques (2 papers), Semantic Web and Ontologies (2 papers), EEG and Brain-Computer Interfaces (2 papers), Genomics and Phylogenetic Studies (2 papers), Biomedical Text Mining and Ontologies (2 papers), Bioinformatics and Genomic Networks (2 papers) and Data Quality and Management (2 papers). The work is most often cited by research in Artificial Intelligence (47 citations), Management Science and Operations Research (12 citations), Signal Processing (8 citations), Health Informatics (1 citation) and Geography, Planning and Development (4 citations). Peter Bloem has collaborated with scholars based in Netherlands and United States. Frequent co-authors include Victor de Boer, Steven de Rooij, Paul Groth, Gerben Klaas Dirk de Vries, Jennifer R. Ramautar, Arthur-Ervin Avrămiea, Simon J. Houtman, Klaus Linkenkaer‐Hansen, Huibert D. Mansvelder and K. Anton Feenstra. Their work appears in journals such as Scientific Reports, Frontiers in Neuroinformatics, Data Mining and Knowledge Discovery, PeerJ Computer Science and eNeuro.
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.