Jonathan Weese

1.1k citations
21 papers · 756 indexed · h-index 11

Jonathan Weese

21 papers receiving 669 citations

Peers

Jonathan Weese
Comparison fields: 5 of 71
  • Artificial Intelligence 638
  • Computer Vision and Pattern Recognition 53
  • Information Systems 54
  • Computer Science Applications 12
  • Urology 13
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Citations per field
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Citations per year

Countries citing papers authored by Jonathan Weese

Since Specialization
Citations

This map shows the geographic impact of Jonathan Weese'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 Jonathan Weese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Weese more than expected).

Fields of papers citing papers by Jonathan Weese

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Weese. 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 Jonathan Weese. The network helps show where Jonathan Weese may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jonathan Weese, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonathan Weese Line = papers co-authored together Jonathan Weese links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20191
2 201826
3 201841
4 20164
5 20156
6 20152
7 20145
8
PARMA: A Predicate Argument Aligner
20139
9
Joshua 5.0: Sparser, Better, Faster, Server
201316
10
Processing Informal, Romanized Pakistani Text Messages
201215
11
Using Categorial Grammar to Label Translation Rules
20125
12
Joshua 4.0: Packing, PRO, and Paraphrases
201223
13
Joshua 3.0: Syntax-based Machine Translation with the Thrax Grammar Extractor
201122
14
cdec: A Decoder‚ Alignment‚ and Learning framework for finite−state and context−free translation models
2010176
15 20106
16
Joshua 2.0: A Toolkit for Parsing-Based Machine Translation with Syntax, Semirings, Discriminative Training and Other Goodies
201013
17 20104
18
Joshua: An open source toolkit for parsing-based machine translation
200960
19 20096
20 2009112

About Jonathan Weese

Jonathan Weese is a scholar working on Artificial Intelligence, Urology, Rheumatology, Nephrology and Genetics, having authored 21 papers that have together received 756 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (15 papers), Topic Modeling (14 papers), Speech and dialogue systems (3 papers), Algorithms and Data Compression (3 papers), Text Readability and Simplification (3 papers), Renal cell carcinoma treatment (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Urological Disorders and Treatments (2 papers). The work is most often cited by research in Artificial Intelligence (638 citations), Computer Vision and Pattern Recognition (53 citations), Information Systems (54 citations), Computer Science Applications (12 citations) and Urology (13 citations). Jonathan Weese has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Juri Ganitkevitch, Chris Callison-Burch, Chris Dyer, Lushan Han, Tim Finin, James Mayfield, Adam Lopez, Lane Schwartz, Omar F. Zaidan and Sanjeev Khudanpur. Their work appears in journals such as Urology, Advances in Urology, SHILAP Revista de lepidopterología, Workshop on Statistical Machine Translation and Edinburgh Research Explorer (University of Edinburgh).

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.

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