Jonathan May

2.8k citations
77 papers · 1.2k · h-index 19

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Text Readability and Simplification
    • Speech and dialogue systems
    • Advanced Text Analysis Techniques
    • Speech Recognition and Synthesis
    • Text and Document Classification Technologies
    • Multimodal Machine Learning Applications

Papers in

Jonathan May

69 papers receiving 1.1k citations

Peers

Jonathan May
Comparison fields: 5 of 86
  • Artificial Intelligence 1.1k
  • Computer Vision and Pattern Recognition 218
  • Management Science and Operations Research 51
  • Information Systems 89
  • Computational Theory and Mathematics 52
Replace Degen Huang with:
Degen Huang China
Hiroya Takamura Japan
Diarmuid Ó Séaghdha United Kingdom
Marina Danilevsky United States
Xinyan Xiao China
Sung-Hyon Myaeng South Korea
Yifei Zhang China
Yi Fang United States
Nicholas Kolkin United States
Maíra Gatti de Bayser Brazil
Jonathan May relative to Degen Huang China Degen Huang's profile →
Citations per field
00.5×3.1×
Degen Huang · 1×
Citations per year

Countries citing papers authored by Jonathan May

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan May

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jonathan May, 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 May Line = papers co-authored together Jonathan May links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017202
2
Tuning as Ranking
2011179
3 202169
4 201866
5 202044
6 201943
7 201738
8 201538
9 201634
10 201032
11
Syntactic Re-Alignment Models for Machine Translation
200728
12
TREC 2002 QA at BBN: Answer Selection and Confidence Estimation.
200228
13 202324
14 201922
15 200920
16 200620
17 201919
18 202019
19 201419
20 201618

About Jonathan May

Jonathan May is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Information Systems and Molecular Biology, having authored 77 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (55 papers), Natural Language Processing Techniques (54 papers), Multimodal Machine Learning Applications (11 papers), Text Readability and Simplification (8 papers), Speech and dialogue systems (7 papers), Semantic Web and Ontologies (5 papers), Speech Recognition and Synthesis (5 papers) and semigroups and automata theory (4 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Computer Vision and Pattern Recognition (218 citations), Management Science and Operations Research (51 citations), Information Systems (89 citations) and Computational Theory and Mathematics (52 citations). Jonathan May has collaborated with scholars based in United States, Germany and Spain. Frequent co-authors include Kevin Knight, Mark Hopkins, Heng Ji, Xiaoman Pan, Boliang Zhang, Joel Nothman, Xiang Ren, Mozhdeh Gheini, Nanyun Peng and Marjan Ghazvininejad. Their work appears in journals such as Language Resources and Evaluation, Computational Linguistics, Biotechnology and Bioengineering, Big Data and British Journal of Industrial Relations.

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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