John McNaught

4.2k total citations · 1 hit paper
84 papers, 2.4k citations indexed

About

John McNaught is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, John McNaught has authored 84 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Artificial Intelligence, 40 papers in Molecular Biology and 12 papers in Information Systems. Recurrent topics in John McNaught's work include Biomedical Text Mining and Ontologies (40 papers), Natural Language Processing Techniques (35 papers) and Semantic Web and Ontologies (31 papers). John McNaught is often cited by papers focused on Biomedical Text Mining and Ontologies (40 papers), Natural Language Processing Techniques (35 papers) and Semantic Web and Ontologies (31 papers). John McNaught collaborates with scholars based in United Kingdom, United States and Japan. John McNaught's co-authors include Sophia Ananiadou, James Thomas, Makoto Miwa, Alison O’Mara-Eves, Paul M. Thompson, Yoshimasa Tsuruoka, Raheel Nawaz, Amit Kumar, ‪Irena Spasić and Yutaka Sasaki and has published in prestigious journals such as Bioinformatics, PLoS ONE and BMC Bioinformatics.

In The Last Decade

John McNaught

80 papers receiving 2.3k citations

Hit Papers

Using text mining for study identification in systematic ... 2015 2026 2018 2022 2015 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John McNaught United Kingdom 25 1.4k 1.1k 391 258 131 84 2.4k
Makoto Miwa Japan 31 3.1k 2.3× 1.6k 1.5× 331 0.8× 328 1.3× 132 1.0× 105 4.3k
Stéfan Darmoni France 22 706 0.5× 738 0.7× 201 0.5× 183 0.7× 47 0.4× 213 1.9k
Prakash M. Nadkarni United States 22 931 0.7× 640 0.6× 44 0.1× 204 0.8× 108 0.8× 83 2.3k
Guido Zuccon Australia 22 1.1k 0.8× 445 0.4× 62 0.2× 479 1.9× 82 0.6× 193 1.7k
Donghyeon Kim South Korea 8 3.0k 2.2× 1.7k 1.6× 76 0.2× 248 1.0× 48 0.4× 24 4.0k
Hong Yu United States 32 3.2k 2.3× 1.9k 1.8× 64 0.2× 360 1.4× 37 0.3× 173 4.5k
Kyle Lo United States 16 1.9k 1.4× 624 0.6× 74 0.2× 314 1.2× 57 0.4× 45 2.5k
Ali Daud Pakistan 29 1.1k 0.8× 202 0.2× 214 0.5× 763 3.0× 84 0.6× 149 3.2k
Kevin Bretonnel Cohen United States 36 2.6k 1.9× 2.8k 2.6× 46 0.1× 291 1.1× 120 0.9× 139 4.4k
Wonjin Yoon South Korea 6 2.9k 2.1× 1.6k 1.5× 62 0.2× 225 0.9× 32 0.2× 13 3.8k

Countries citing papers authored by John McNaught

Since Specialization
Citations

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

Fields of papers citing papers by John McNaught

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John McNaught

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

All Works

20 of 20 papers shown
1.
Przybyła, Piotr, Matthew Shardlow, Sophie Aubin, et al.. (2016). Text mining resources for the life sciences. Database. 2016. 38 indexed citations
2.
Thompson, Paul M., Riza Batista-Navarro, Georgios Kontonatsios, et al.. (2016). Text Mining the History of Medicine. PLoS ONE. 11(1). e0144717–e0144717. 37 indexed citations
3.
Thompson, Paul M., Raheel Nawaz, John McNaught, & Sophia Ananiadou. (2011). Enriching a biomedical event corpus with meta-knowledge annotation. BMC Bioinformatics. 12(1). 393–393. 55 indexed citations
4.
Ananiadou, Sophia, John McNaught, James Thomas, Mark Rickinson, & Sandy Oliver. (2010). Evaluating a text mining based educational search portal. Language Resources and Evaluation. 3344–3350. 3 indexed citations
5.
Nawaz, Raheel, Paul M. Thompson, John McNaught, & Sophia Ananiadou. (2010). Meta-knowledge annotation of bio-events. Language Resources and Evaluation. 2498–2505. 28 indexed citations
6.
Thompson, Paul M., Syed Amir Iqbal, John McNaught, & Sophia Ananiadou. (2009). Construction of an annotated corpus to support biomedical information extraction. BMC Bioinformatics. 10(1). 349–349. 85 indexed citations
7.
Thompson, Paul M., Philip D. Cotter, John McNaught, et al.. (2008). Building a Bio-Event Annotated Corpus for the Acquisition of Semantic Frames from Biomedical Corpora. Language Resources and Evaluation. 2159–2166. 8 indexed citations
8.
Rebholz‐Schuhmann, Dietrich, Piotr Pęzik, Jang‐Joo Kim, et al.. (2008). BioLexicon: Towards a Reference Terminological Resource in the Biomedical Domain. Research Explorer (The University of Manchester). 9 indexed citations
9.
Sasaki, Yutaka, Simonetta Montemagni⋄, Piotr Pęzik, et al.. (2008). BioLexicon: A Lexical Resource for the Biology Domain. 26 indexed citations
10.
Thompson, Paul M., Giulia Venturi⋄, John McNaught, Simonetta Montemagni⋄, & Sophia Ananiadou. (2008). Categorising Modality in Biomedical Texts. Language Resources and Evaluation. 27–34. 29 indexed citations
11.
Piao, Scott, John McNaught, & Sophia Ananiadou. (2008). Clustering Related Terms with Definitions. Language Resources and Evaluation. 2013–2019. 1 indexed citations
12.
Sasaki, Yutaka, Yoshimasa Tsuruoka, John McNaught, & Sophia Ananiadou. (2008). How to make the most of NE dictionaries in statistical NER. BMC Bioinformatics. 9(S11). S5–S5. 33 indexed citations
13.
Tsuruoka, Yoshimasa, John McNaught, & Sophia Ananiadou. (2008). Normalizing biomedical terms by minimizing ambiguity and variability. BMC Bioinformatics. 9(S3). S2–S2. 47 indexed citations
14.
Ananiadou, Sophia & John McNaught. (2005). Text Mining for Biology And Biomedicine. 236 indexed citations
15.
Zervanou, Kalliopi & John McNaught. (2004). A domain-independent approach to IE rule development. Language Resources and Evaluation. 745–748. 3 indexed citations
16.
Castillo, Gabriel, Gerardo Sierra, & John McNaught. (2003). An improved algorithm for semantic clustering. 304–309. 2 indexed citations
17.
McNaught, John. (1988). Computers and terminology. Research Explorer (The University of Manchester). 1 indexed citations
18.
Bennett, Paul, et al.. (1986). Multilingual Aspects of Information Technology. 4 indexed citations
19.
Sager, Juan C., Harold Somers, & John McNaught. (1982). Thesaurus integration in the social sciences:Part II: Stages towards integration. Research Explorer (The University of Manchester). 1 indexed citations
20.
Sager, Juan C., Harold Somers, & John McNaught. (1981). Guidelines for the establishment of comparison and compatibility matrices between thesauri in the social sciences. UNESCO eBooks. 1 indexed citations

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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