Rob Koeling
- Artificial Intelligence top 2%
- Molecular Biology
- Health Information Management top 5%
- Information Systems top 10%
- Epidemiology
- Co-authors
- Diana McCarthyJohn CarrollJulie WeedsJackie CassellA. Rosemary TateMark-Jan NederhofGosse BoumaGertjan van Noord
- Topics
- Natural Language Processing Techniques (20 papers)Topic Modeling (17 papers)Speech and dialogue systems (9 papers)
- Partner nations
- United KingdomUnited StatesNetherlands
In The Last Decade
Rob Koeling
26 papers receiving 618 citations
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 606
- Molecular Biology 104
- Health Information Management 48
- Information Systems 48
- Epidemiology 26
Countries citing papers authored by Rob Koeling
This map shows the geographic impact of Rob Koeling'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 Rob Koeling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rob Koeling more than expected).
Fields of papers citing papers by Rob Koeling
This network shows the impact of papers produced by Rob Koeling. 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 Rob Koeling. The network helps show where Rob Koeling may publish in the future.
Co-authorship network of co-authors of Rob Koeling
This figure shows the co-authorship network connecting the top 25 collaborators of Rob Koeling. A scholar is included among the top collaborators of Rob Koeling based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rob Koeling. Rob Koeling is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 20 | |
| 4 | 27 | |
| 5 | 51 | |
| 6 | Corpus Annotation as a Scientific Task | 2 |
| 7 | 25 | |
| 8 | Gloss-Based Semantic Similarity Metrics for Predominant Sense Acquisition | 4 |
| 9 | 79 | |
| 10 | Cross-language acquisition of semantic models for verbal predicates | 2 |
| 11 | Using automatically acquired predominant senses for word sense disambiguation | 23 |
| 12 | 207 | |
| 13 | Ranking WordNet Senses Automatically | 12 |
| 14 | 3 | |
| 15 | 3 | |
| 16 | 3 | |
| 17 | 4 | |
| 18 | 51 | |
| 19 | 44 | |
| 20 | 6 |
About Rob Koeling
Rob Koeling is a scholar working on Artificial Intelligence, Health Information Management and Language and Linguistics, having authored 26 papers that have together received 720 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (20 papers), Topic Modeling (17 papers) and Speech and dialogue systems (9 papers). The work is most often cited by research in Artificial Intelligence (606 citations), Health Information Management (48 citations) and Issues, ethics and legal aspects (4 citations). Rob Koeling has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Diana McCarthy, John Carroll, Julie Weeds, Jackie Cassell, A. Rosemary Tate, Mark-Jan Nederhof, Gosse Bouma, Gertjan van Noord, Amanda Nicholson and Greta Rait. Their work appears in journals such as BMC Medical Research Methodology, BMJ Open and Computational Linguistics.
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.