Tom M. Mitchell
Impact in
- Artificial Intelligence top 0.01%
- Topic Modeling
- Natural Language Processing Techniques
- Text and Document Classification Technologies
- Machine Learning and Algorithms
- Machine Learning and Data Classification
- AI-based Problem Solving and Planning
- Semantic Web and Ontologies
- Domain Adaptation and Few-Shot Learning
- Health Informatics top 0.2%
Papers in
-
- Topic Modeling 61
- Natural Language Processing Techniques 50
- Machine Learning and Algorithms 26
- AI-based Problem Solving and Planning 21
- Semantic Web and Ontologies 14
-
- Neurobiology of Language and Bilingualism 13
- Functional Brain Connectivity Studies 12
- Face Recognition and Perception 11
- Co-authors
- Michael I. Jordan (1 shared paper)Avrim Blum (2 shared papers)Sebastian Thrun (6 shared papers)Kamal Nigam (3 shared papers)Andrew Kachites McCallum (1 shared paper)Erik Brynjolfsson (4 shared papers)Francisco Pereira (1 shared paper)Matthew Botvinick (1 shared paper)
- Journals
- NeuroImage (5 papers)Science (5 papers)PLoS ONE (4 papers)AI Magazine (4 papers)Artificial Intelligence (3 papers)
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
Tom M. Mitchell
197 papers receiving 26.4k citations
Tom M. Mitchell's Hit Papers
Peers
Comparison fields: 5 of 236
- Artificial Intelligence 14.6k
- Health Informatics 286
- Computational Mathematics 126
- Computer Vision and Pattern Recognition 3.9k
- Cognitive Neuroscience 2.9k
Countries citing papers authored by Tom M. Mitchell
This map shows the geographic impact of Tom M. Mitchell'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 Tom M. Mitchell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom M. Mitchell more than expected).
Fields of papers citing papers by Tom M. Mitchell
This network shows the impact of papers produced by Tom M. Mitchell. 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 Tom M. Mitchell. The network helps show where Tom M. Mitchell may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom M. Mitchell, 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 203 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Machine learning: Trends, perspectives, and prospects Hit paper breakdown → | 2015 | 6287 |
| 2 | Combining labeled and unlabeled data with co-training Hit paper breakdown → | 1998 | 3660 |
| 3 | Text Classification from Labeled and Unlabeled Documents using EM Hit paper breakdown → | 2000 | 1871 |
| 4 | Global Analysis of Protein Activities Using Proteome Chips Hit paper breakdown → | 2001 | 1502 |
| 5 | Machine learning classifiers and fMRI: A tutorial overview Hit paper breakdown → | 2008 | 1241 |
| 6 | Toward an Architecture for Never-Ending Language Learning Hit paper breakdown → | 2010 | 1189 |
| 7 | Predicting Human Brain Activity Associated with the Meanings of Nouns Hit paper breakdown → | 2008 | 808 |
| 8 | Generalization as search Hit paper breakdown → | 1982 | 807 |
| 9 | Explanation-Based Generalization: A Unifying View Hit paper breakdown → | 1986 | 664 |
| 10 | What can machine learning do? Workforce implications Hit paper breakdown → | 2017 | 632 |
| 11 | 1999 | 441 | |
| 12 | Web Watcher: A Tour Guide for the World Wide Web. | 1997 | 424 |
| 13 | 1986 | 409 | |
| 14 | What Can Machines Learn and What Does It Mean for Occupations and the Economy? Hit paper breakdown → | 2018 | 320 |
| 15 | Zero-Shot Learning with Semantic Output Codes Hit paper breakdown → | 2018 | 294 |
| 16 | 2000 | 286 | |
| 17 | 1995 | 273 | |
| 18 | 2010 | 272 | |
| 19 | 1994 | 248 | |
| 20 | Learning to classify text from labeled and unlabeled documents | 1998 | 220 |
About Tom M. Mitchell
Tom M. Mitchell is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Information Systems, Computer Vision and Pattern Recognition and Developmental and Educational Psychology, having authored 203 papers that have together received 28.4k indexed citations. Recurring topics across this work include Topic Modeling (61 papers), Natural Language Processing Techniques (50 papers), Machine Learning and Algorithms (26 papers), AI-based Problem Solving and Planning (21 papers), Semantic Web and Ontologies (14 papers), Neurobiology of Language and Bilingualism (13 papers), Functional Brain Connectivity Studies (12 papers) and Face Recognition and Perception (11 papers). The work is most often cited by research in Artificial Intelligence (14.6k citations), Health Informatics (286 citations), Computational Mathematics (126 citations), Computer Vision and Pattern Recognition (3.9k citations) and Cognitive Neuroscience (2.9k citations). Tom M. Mitchell has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Michael I. Jordan, Avrim Blum, Sebastian Thrun, Kamal Nigam, Andrew Kachites McCallum, Erik Brynjolfsson, Francisco Pereira, Matthew Botvinick, J. Andrew Carlson and Smadar T. Kedar-Cabelli. Their work appears in journals such as NeuroImage, Science, PLoS ONE, AI Magazine and Artificial Intelligence.
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.