Linnea Micciulla

2.5k citations
5 papers · 1.6k indexed · 1 hit paper · h-index 4
Topics
Topic Modeling (5 papers)Natural Language Processing Techniques (4 papers)Semantic Web and Ontologies (2 papers)
Journals
Joint Conference on Lexical and Computational SemanticsConference of the Association for Machine Translation in the Americas
Partner nations
United States

In The Last Decade

Linnea Micciulla

5 papers receiving 1.3k citations

Hit Papers

A Study of Translation Edit Rate with Targeted Human Anno...2006202620122019200650010001.5k

Peers

Linnea Micciulla
Comparison fields: 5 of 41
  • Artificial Intelligence 1.6k
  • Computer Vision and Pattern Recognition 214
  • Information Systems 122
  • Language and Linguistics 98
  • Molecular Biology 92
Replace Matthew Snover with:
Matthew Snover United States
George Foster Canada
Martin Volk Switzerland
Philippe Langlais Canada
Kiyotaka Uchimoto Japan
Spence Green United States
I. Dan Melamed United States
Christoph Tillmann United States
Marine Carpuat United States
Alexander Fraser Germany
Linnea Micciulla relative to Matthew Snover United States Matthew Snover's profile →
Citations per field
00.5×1.5×
Matthew Snover · 1×
Citations per year

Countries citing papers authored by Linnea Micciulla

Since Specialization
Citations

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

Fields of papers citing papers by Linnea Micciulla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linnea Micciulla

This figure shows the co-authorship network connecting the top 25 collaborators of Linnea Micciulla. A scholar is included among the top collaborators of Linnea Micciulla 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 Linnea Micciulla. Linnea Micciulla is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
#WorkIndexed citations
1 16
2 10
3 27
4
A Study of Translation Edit Rate with Targeted Human Annotationbreakdown →
1590
5 1

About Linnea Micciulla

Linnea Micciulla is a scholar working on Artificial Intelligence, Infectious Diseases and Organic Chemistry, having authored 5 papers that have together received 1.6k indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Artificial Intelligence (1.6k citations), Computer Vision and Pattern Recognition (214 citations) and Language and Linguistics (98 citations). Linnea Micciulla has collaborated with scholars based in United States. Frequent co-authors include Richard Schwartz, John Makhoul, Matthew Snover, Bonnie J. Dorr, Ralph Weischedel, Sameer Pradhan, Lance Ramshaw, Richard E. Crowell, Yvette J. Tenney and Katherine Godfrey. Their work appears in journals such as Joint Conference on Lexical and Computational Semantics and Conference of the Association for Machine Translation in the Americas.

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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