John Dunnion

608 citations
27 papers · 272 · h-index 10

Impact in

Papers in

John Dunnion

27 papers receiving 254 citations

Peers

John Dunnion
Comparison fields: 5 of 111
  • Animal Science and Zoology 37
  • Small Animals 25
  • Agronomy and Crop Science 34
  • Artificial Intelligence 98
  • Health Informatics 3
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Citations per year

Countries citing papers authored by John Dunnion

Since Specialization
Citations

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

Fields of papers citing papers by John Dunnion

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside John Dunnion, 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 John Dunnion Line = papers co-authored together John Dunnion links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201782
2 201731
3 201220
4 201016
5 200413
6 201712
7 200310
8
A comparison of machine learning techniques for predicting insemination outcome in Irish dairy cows
20169
9 19869
10
Comparing Lexical Chain-based Summarisation Approaches Using an Extrinsic Evaluation
20049
11 20128
12 20087
13
Comparing Redundancy Removal Techniques for Multi–Document Summarisation
20046
14 20175
15
News Story Gisting at University College Dublin
20045
16
UCD IIRG at TAC 2010 KBP Slot Filling Task
20104
17
Constructing conceptual graphs using linguistic resources
20054
18 20074
19
Machine Learning Approach to Augmenting News Headline Generation
20054
20
IIRG: A Naive Approach to Evaluating Phrasal Semantics
20133

About John Dunnion

John Dunnion is a scholar working on Artificial Intelligence, Signal Processing, Genetics, Agronomy and Crop Science and Computer Networks and Communications, having authored 27 papers that have together received 272 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Natural Language Processing Techniques (8 papers), Data Management and Algorithms (6 papers), Genetic and phenotypic traits in livestock (6 papers), Advanced Text Analysis Techniques (5 papers), Semantic Web and Ontologies (5 papers), Reproductive Physiology in Livestock (5 papers) and Advanced Database Systems and Queries (4 papers). The work is most often cited by research in Animal Science and Zoology (37 citations), Small Animals (25 citations), Agronomy and Crop Science (34 citations), Artificial Intelligence (98 citations) and Health Informatics (3 citations). John Dunnion has collaborated with scholars based in Ireland, Australia and United States. Frequent co-authors include Luke O’Grady, Michael L. Doherty, S.T. Butler, Joe Carthy, David Lillis, Rem Collier, Fergus Toolan, Nicola Stokes, John F. Mee and L. Shalloo. Their work appears in journals such as Artificial Intelligence Review, Journal of Dairy Science, Information Processing & Management, Irish Veterinary Journal and Theory and applications of categories.

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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