Kevin Small
Impact in
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- Meta-analysis and systematic reviews
- Artificial Intelligence top 2%
- Topic Modeling
- Machine Learning and Algorithms
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Text and Document Classification Technologies
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
Papers in
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- Topic Modeling 14
- Machine Learning and Algorithms 11
- Natural Language Processing Techniques 10
- Machine Learning and Data Classification 6
- Text and Document Classification Technologies 4
- Domain Adaptation and Few-Shot Learning 3
- Bayesian Modeling and Causal Inference 3
- Algorithms and Data Compression 3
- Co-authors
- Thomas A Trikalinos (11 shared papers)Byron Wallace (9 shared papers)Carla E. Brodley (8 shared papers)Dan Roth (14 shared papers)Joseph Lau (3 shared papers)Alexandre Klementiev (5 shared papers)Christopher H. Schmid (4 shared papers)Ivan S. Titov (3 shared papers)
- Journals
- AI Magazine (1 paper)Journal of Machine Learning Research (1 paper)Research Synthesis Methods (1 paper)Theory and applications of categories (1 paper)Medical Decision Making (1 paper)
- Partner nations
- United StatesGermanyNepal
In The Last Decade
Kevin Small
34 papers receiving 1.3k citations
Kevin Small's Hit Papers
Peers
Comparison fields: 5 of 158
- Statistics, Probability and Uncertainty 135
- Artificial Intelligence 631
- Health Informatics 19
- Computer Science Applications 44
- Signal Processing 68
Countries citing papers authored by Kevin Small
This map shows the geographic impact of Kevin Small'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 Kevin Small with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Small more than expected).
Fields of papers citing papers by Kevin Small
This network shows the impact of papers produced by Kevin Small. 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 Kevin Small. The network helps show where Kevin Small may publish in the future.
Co-authors
The 25 scholars most cited alongside Kevin Small, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deploying an interactive machine learning system in an evidence-based practice center Hit paper breakdown → | 2012 | 444 |
| 2 | 2011 | 135 | |
| 3 | 2006 | 104 | |
| 4 | 2010 | 80 | |
| 5 | 2008 | 65 | |
| 6 | Sentence Emotion Analysis and Recognition Based on Emotion Words Using Ren-CECps ∗ | 2010 | 60 |
| 7 | 2012 | 49 | |
| 8 | 2011 | 48 | |
| 9 | 2007 | 47 | |
| 10 | The Constrained Weight Space SVM: Learning with Ranked Features | 2011 | 31 |
| 11 | 2010 | 29 | |
| 12 | Unsupervised rank aggregation with domain-specific expertise | 2009 | 28 |
| 13 | 2014 | 26 | |
| 14 | 2012 | 23 | |
| 15 | Relation Alignment for Textual Entailment Recognition. | 2009 | 20 |
| 16 | The Role of Semantic Information in Learning Question Classifiers | 2004 | 20 |
| 17 | 2010 | 18 | |
| 18 | 2021 | 17 | |
| 19 | 2009 | 15 | |
| 20 | Question-Answering via Enhanced Understanding of Questions. | 2002 | 15 |
About Kevin Small
Kevin Small is a scholar working on Artificial Intelligence, Statistics, Probability and Uncertainty, Computer Vision and Pattern Recognition, Information Systems and Management Science and Operations Research, having authored 35 papers that have together received 1.3k indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Machine Learning and Algorithms (11 papers), Natural Language Processing Techniques (10 papers), Machine Learning and Data Classification (6 papers), Text and Document Classification Technologies (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Bayesian Modeling and Causal Inference (3 papers) and Algorithms and Data Compression (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (135 citations), Artificial Intelligence (631 citations), Health Informatics (19 citations), Computer Science Applications (44 citations) and Signal Processing (68 citations). Kevin Small has collaborated with scholars based in United States, Germany and Nepal. Frequent co-authors include Thomas A Trikalinos, Byron Wallace, Carla E. Brodley, Dan Roth, Joseph Lau, Alexandre Klementiev, Christopher H. Schmid, Ivan S. Titov, Li Zhou and Xin Li. Their work appears in journals such as AI Magazine, Journal of Machine Learning Research, Research Synthesis Methods, Theory and applications of categories and Medical Decision Making.
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.