Rebecca Knowles

1.5k total citations
35 papers, 769 citations indexed

About

Rebecca Knowles is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Psychiatry and Mental health. According to data from OpenAlex, Rebecca Knowles has authored 35 papers receiving a total of 769 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 6 papers in Psychiatry and Mental health. Recurrent topics in Rebecca Knowles's work include Topic Modeling (18 papers), Natural Language Processing Techniques (18 papers) and Multimodal Machine Learning Applications (6 papers). Rebecca Knowles is often cited by papers focused on Topic Modeling (18 papers), Natural Language Processing Techniques (18 papers) and Multimodal Machine Learning Applications (6 papers). Rebecca Knowles collaborates with scholars based in United States, United Kingdom and Canada. Rebecca Knowles's co-authors include Nicholas Tarrier, Georgina Rowse, Simon McCarthy‐Jones, Philipp Koehn, Richard P. Bentall, Sara Tai, Steven Jones, Andrew R. Thompson, Mike Marriott and Mark Dredze and has published in prestigious journals such as Critical Care Medicine, Clinical Psychology Review and Journal of Antimicrobial Chemotherapy.

In The Last Decade

Rebecca Knowles

34 papers receiving 728 citations

Peers

Rebecca Knowles
Comparison fields: 5 of 103
  • Psychiatry and Mental health 207
  • Artificial Intelligence 182
  • Clinical Psychology 163
  • Radiological and Ultrasound Technology 127
  • Critical Care and Intensive Care Medicine 120
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Citations per field, relative to Rebecca Knowles
Rebecca Knowles · 1×
Citations per year, relative to Rebecca Knowles
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Countries citing papers authored by Rebecca Knowles

Since Specialization
Citations

This map shows the geographic impact of Rebecca Knowles'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 Rebecca Knowles with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rebecca Knowles more than expected).

Fields of papers citing papers by Rebecca Knowles

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rebecca Knowles. 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 Rebecca Knowles. The network helps show where Rebecca Knowles may publish in the future.

Co-authorship network of co-authors of Rebecca Knowles

This figure shows the co-authorship network connecting the top 25 collaborators of Rebecca Knowles. A scholar is included among the top collaborators of Rebecca Knowles 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 Rebecca Knowles. Rebecca Knowles is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 9
2 3
3 18
4 54
5 9
6 5
7 3
8
The Nunavut Hansard Inuktitut-English Parallel Corpus 3.0 with Preliminary Machine Translation Results.
20
9 15
10 7
11
Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning (CoNLL)
10
12 3
13 25
14 4
15 0
16 7
17 37
18 8
19 154
20 106

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.

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