Ryan McDonald
Impact in
- Artificial Intelligence top 0.05%
- Topic Modeling
- Natural Language Processing Techniques
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Text Readability and Simplification
- Text and Document Classification Technologies
- Speech and dialogue systems
- Semantic Web and Ontologies
- Information Systems top 0.5%
Papers in
-
- Topic Modeling 61
- Natural Language Processing Techniques 56
- Sentiment Analysis and Opinion Mining 10
- Semantic Web and Ontologies 10
- Advanced Text Analysis Techniques 8
- Speech and dialogue systems 7
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- Biomedical Text Mining and Ontologies 11
- Co-authors
- Fernando Pereira (12 shared papers)Joakim Nivre (16 shared papers)Ivan Titov (2 shared papers)Slav Petrov (9 shared papers)John Blitzer (1 shared paper)Koby Crammer (3 shared papers)Jan Hajič (2 shared papers)Dipanjan Das (3 shared papers)
- Journals
- Synthesis lectures on human language technologies (5 papers)Transactions of the Association for Computational Linguistics (3 papers)BMC Bioinformatics (3 papers)Language Resources and Evaluation (2 papers)Computational Linguistics (2 papers)
- Partner nations
- United StatesSwedenUnited Kingdom
In The Last Decade
Ryan McDonald
77 papers receiving 9.5k citations
Ryan McDonald's Hit Papers
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 9.8k
- Information Systems 1.2k
- Computer Vision and Pattern Recognition 923
- General Social Sciences 80
- Language and Linguistics 216
Countries citing papers authored by Ryan McDonald
This map shows the geographic impact of Ryan McDonald'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 Ryan McDonald with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan McDonald more than expected).
Fields of papers citing papers by Ryan McDonald
This network shows the impact of papers produced by Ryan McDonald. 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 Ryan McDonald. The network helps show where Ryan McDonald may publish in the future.
Co-authors
The 25 scholars most cited alongside Ryan McDonald, 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 78 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Domain adaptation with structural correspondence learning Hit paper breakdown → | 2006 | 1120 |
| 2 | Universal Dependencies v1: A Multilingual Treebank Collection Hit paper breakdown → | 2016 | 638 |
| 3 | Non-projective dependency parsing using spanning tree algorithms Hit paper breakdown → | 2005 | 616 |
| 4 | Online large-margin training of dependency parsers Hit paper breakdown → | 2005 | 612 |
| 5 | Modeling online reviews with multi-grain topic models Hit paper breakdown → | 2008 | 586 |
| 6 | The CoNLL 2007 Shared Task on Dependency Parsing Hit paper breakdown → | 2007 | 495 |
| 7 | A Joint Model of Text and Aspect Ratings for Sentiment Summarization Hit paper breakdown → | 2008 | 482 |
| 8 | A Universal Part-of-Speech Tagset Hit paper breakdown → | 2012 | 463 |
| 9 | Online Learning of Approximate Dependency Parsing Algorithms. | 2006 | 371 |
| 10 | Building a Sentiment Summarizer for Local Service Reviews | 2008 | 295 |
| 11 | Universal Dependency Annotation for Multilingual Parsing | 2013 | 282 |
| 12 | 2007 | 266 | |
| 13 | Dependency Parsing | 2009 | 257 |
| 14 | Structured Models for Fine-to-Coarse Sentiment Analysis | 2007 | 219 |
| 15 | Characterizing the Errors of Data-Driven Dependency Parsing Models | 2007 | 203 |
| 16 | Multi-Source Transfer of Delexicalized Dependency Parsers | 2011 | 196 |
| 17 | 2005 | 181 | |
| 18 | Integrating Graph-Based and Transition-Based Dependency Parsers | 2008 | 180 |
| 19 | Distributed Training Strategies for the Structured Perceptron | 2010 | 167 |
| 20 | 2006 | 157 |
About Ryan McDonald
Ryan McDonald is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Information Systems and Ocean Engineering, having authored 78 papers that have together received 10.5k indexed citations. Recurring topics across this work include Topic Modeling (61 papers), Natural Language Processing Techniques (56 papers), Biomedical Text Mining and Ontologies (11 papers), Sentiment Analysis and Opinion Mining (10 papers), Semantic Web and Ontologies (10 papers), Advanced Text Analysis Techniques (8 papers), Speech and dialogue systems (7 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Artificial Intelligence (9.8k citations), Information Systems (1.2k citations), Computer Vision and Pattern Recognition (923 citations), General Social Sciences (80 citations) and Language and Linguistics (216 citations). Ryan McDonald has collaborated with scholars based in United States, Sweden and United Kingdom. Frequent co-authors include Fernando Pereira, Joakim Nivre, Ivan Titov, Slav Petrov, John Blitzer, Koby Crammer, Jan Hajič, Dipanjan Das, Sandra Kübler and Oscar Täckström. Their work appears in journals such as Synthesis lectures on human language technologies, Transactions of the Association for Computational Linguistics, BMC Bioinformatics, Language Resources and Evaluation 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.