John C. Blitzer
Impact in
- Artificial Intelligence top 0.05%
- Domain Adaptation and Few-Shot Learning
- Sentiment Analysis and Opinion Mining
- Natural Language Processing Techniques
- Topic Modeling
- Advanced Text Analysis Techniques
- Machine Learning and Algorithms
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- Face and Expression Recognition
Papers in
-
- Domain Adaptation and Few-Shot Learning 8
- Natural Language Processing Techniques 8
- Advanced Text Analysis Techniques 4
- Machine Learning and Algorithms 2
- Topic Modeling 2
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- Personal Information Management and User Behavior 4
- Co-authors
- Fernando M. B. Pereira (11 shared papers)Koby Crammer (3 shared papers)Shai Ben-David (2 shared papers)Kilian Q. Weinberger (3 shared papers)Mark H. Dredze (6 shared papers)Lawrence K. Saul (2 shared papers)Alex Kulesza (2 shared papers)Jennifer Wortman Vaughan (1 shared paper)
- Journals
- Language Resources and Evaluation (1 paper)Political Analysis (1 paper)Machine Learning (1 paper)Singapore Management University Institutional Knowledge (InK) (Singapore Management University) (2 papers)Scholarly Commons (University of Pennsylvania) (1 paper)
- Partner nations
- United StatesHong KongUnited Kingdom
In The Last Decade
John C. Blitzer
30 papers receiving 8.9k citations
John C. Blitzer's Hit Papers
Peers
Comparison fields: 5 of 129
- Artificial Intelligence 6.8k
- Computer Vision and Pattern Recognition 1.4k
- Media Technology 138
- Information Systems 387
- Signal Processing 121
Countries citing papers authored by John C. Blitzer
This map shows the geographic impact of John C. Blitzer'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 John C. Blitzer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John C. Blitzer more than expected).
Fields of papers citing papers by John C. Blitzer
This network shows the impact of papers produced by John C. Blitzer. 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 John C. Blitzer. The network helps show where John C. Blitzer may publish in the future.
Co-authors
The 25 scholars most cited alongside John C. Blitzer, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A theory of learning from different domains Hit paper breakdown → | 2009 | 2410 |
| 2 | Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification Hit paper breakdown → | 2007 | 1524 |
| 3 | Analysis of Representations for Domain Adaptation Hit paper breakdown → | 2007 | 1414 |
| 4 | Distance Metric Learning for Large Margin Nearest Neighbor Classification Hit paper breakdown → | 2005 | 1353 |
| 5 | Domain adaptation with structural correspondence learning Hit paper breakdown → | 2006 | 1148 |
| 6 | Co-Training for Domain Adaptation | 2011 | 279 |
| 7 | 2004 | 256 | |
| 8 | Learning Bounds for Domain Adaptation | 2007 | 242 |
| 9 | 2003 | 104 | |
| 10 | 2009 | 79 | |
| 11 | Domain Adaptation with Coupled Subspaces | 2011 | 78 |
| 12 | Frustratingly Hard Domain Adaptation for Dependency Parsing | 2007 | 60 |
| 13 | Joint Parsing and Alignment with Weakly Synchronized Grammars | 2010 | 37 |
| 14 | Domain adaptation of natural language processing systems | 2008 | 36 |
| 15 | Regularized Learning with Networks of Features | 2008 | 32 |
| 16 | 2008 | 28 | |
| 17 | Learning Better Monolingual Models with Unannotated Bilingual Text | 2010 | 28 |
| 18 | Hierarchical Distributed Representations for Statistical Language Modeling | 2004 | 23 |
| 19 | 2003 | 22 | |
| 20 | Intelligent email: aiding users with AI | 2008 | 17 |
About John C. Blitzer
John C. Blitzer is a scholar working on Artificial Intelligence, Information Systems and Management, Information Systems, Computer Vision and Pattern Recognition and Political Science and International Relations, having authored 30 papers that have together received 9.3k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (8 papers), Natural Language Processing Techniques (8 papers), Advanced Text Analysis Techniques (4 papers), Personal Information Management and User Behavior (4 papers), Information Retrieval and Search Behavior (3 papers), Spam and Phishing Detection (2 papers), Machine Learning and Algorithms (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Artificial Intelligence (6.8k citations), Computer Vision and Pattern Recognition (1.4k citations), Media Technology (138 citations), Information Systems (387 citations) and Signal Processing (121 citations). John C. Blitzer has collaborated with scholars based in United States, Hong Kong and United Kingdom. Frequent co-authors include Fernando M. B. Pereira, Koby Crammer, Shai Ben-David, Kilian Q. Weinberger, Mark H. Dredze, Lawrence K. Saul, Alex Kulesza, Jennifer Wortman Vaughan, Ryan McDonald and Minmin Chen. Their work appears in journals such as Language Resources and Evaluation, Political Analysis, Machine Learning, Singapore Management University Institutional Knowledge (InK) (Singapore Management University) and Scholarly Commons (University of Pennsylvania).
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.