Matthew Snover
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Language and Linguistics top 5%
- Molecular Biology
- Co-authors
- Bonnie J. DorrRichard SchwartzLinnea MicciullaJohn MakhoulNitin MadnaniMichael R. BrentGaja JaroszHeng Ji
- Topics
- Natural Language Processing Techniques (16 papers)Topic Modeling (15 papers)Speech and dialogue systems (6 papers)
- Journals
- Machine TranslationTheory and applications of categoriesEmpirical Methods in Natural Language Processing
- Partner nations
- United States
In The Last Decade
Matthew Snover
18 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 2.1k
- Computer Vision and Pattern Recognition 255
- Information Systems 156
- Language and Linguistics 113
- Molecular Biology 109
Countries citing papers authored by Matthew Snover
This map shows the geographic impact of Matthew Snover'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 Matthew Snover with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Snover more than expected).
Fields of papers citing papers by Matthew Snover
This network shows the impact of papers produced by Matthew Snover. 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 Matthew Snover. The network helps show where Matthew Snover may publish in the future.
Co-authorship network of co-authors of Matthew Snover
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Snover. A scholar is included among the top collaborators of Matthew Snover 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 Matthew Snover. Matthew Snover is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | Cross-lingual Slot Filling from Comparable Corpora | 3 |
| 5 | Unsupervised Language-Independent Name Translation Mining from Wikipedia Infoboxes | 12 |
| 6 | CUNY-BLENDER TAC-KBP2010 Entity Linking and Slot Filling System Description | 39 |
| 7 | 141 | |
| 8 | Exploring Different Human Judgments with a Tunable MT Metric | 1 |
| 9 | 108 | |
| 10 | 6 | |
| 11 | 49 | |
| 12 | A Study of Translation Edit Rate with Targeted Human Annotationbreakdown → | 1590 |
| 13 | 34 | |
| 14 | 11 | |
| 15 | SParseval: Evaluation metrics for parsing speech | 29 |
| 16 | 34 | |
| 17 | A Probabilistic Model for Learning Concatenative Morphology | 14 |
| 18 | 9 | |
| 19 | 33 | |
| 20 | 37 |
About Matthew Snover
Matthew Snover is a scholar working on Artificial Intelligence, Signal Processing and Information Systems, having authored 20 papers that have together received 2.2k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (16 papers), Topic Modeling (15 papers) and Speech and dialogue systems (6 papers). The work is most often cited by research in Artificial Intelligence (2.1k citations), Computer Vision and Pattern Recognition (255 citations) and Language and Linguistics (113 citations). Matthew Snover has collaborated with scholars based in United States. Frequent co-authors include Bonnie J. Dorr, Richard Schwartz, Linnea Micciulla, John Makhoul, Nitin Madnani, Michael R. Brent, Richard Schwartz, Gaja Jarosz, Heng Ji and Yang Liu. Their work appears in journals such as Machine Translation, Theory and applications of categories and Empirical Methods in Natural Language Processing.
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.