Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of James Curran'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 James Curran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Curran more than expected).
This network shows the impact of papers produced by James Curran. 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 James Curran. The network helps show where James Curran may publish in the future.
Co-authorship network of co-authors of James Curran
This figure shows the co-authorship network connecting the top 25 collaborators of James Curran.
A scholar is included among the top collaborators of James Curran 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 James Curran. James Curran is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Curran, James, et al.. (2014). docrep: A lightweight and efficient document representation framework. International Conference on Computational Linguistics. 762–771.5 indexed citations
3.
Kummerfeld, Jonathan K., Daniel Tse, James Curran, & Dan Klein. (2013). An Empirical Examination of Challenges in Chinese Parsing. Meeting of the Association for Computational Linguistics. 98–103.11 indexed citations
4.
O’Keefe, Tim, et al.. (2013). An annotated corpus of quoted opinions in news articles. Meeting of the Association for Computational Linguistics. 516–520.6 indexed citations
5.
Radford, Will & James Curran. (2013). Joint Apposition Extraction with Syntactic and Semantic Constraints. Meeting of the Association for Computational Linguistics. 671–677.3 indexed citations
6.
Lister, Raymond, Daryl D’Souza, Margaret Hamilton, et al.. (2012). Toward a shared understanding of competency in programming: An invitation to the BABELnot project. QUT ePrints (Queensland University of Technology).12 indexed citations
7.
Curran, James, et al.. (2012). Improvements to Training an RNN parser. International Conference on Computational Linguistics. 279–294.1 indexed citations
8.
Tse, Daniel & James Curran. (2012). The Challenges of Parsing Chinese with Combinatory Categorial Grammar. North American Chapter of the Association for Computational Linguistics. 295–304.8 indexed citations
9.
Kummerfeld, Jonathan K., David Hall, James Curran, & Dan Klein. (2012). Parser Showdown at the Wall Street Corral: An Empirical Investigation of Error Types in Parser Output. Empirical Methods in Natural Language Processing. 1048–1059.50 indexed citations
10.
Nothman, Joel, Matthew Honnibal, Ben Hachey, & James Curran. (2012). Event Linking: Grounding Event Reference in a News Archive. Meeting of the Association for Computational Linguistics. 228–232.17 indexed citations
11.
Curran, James. (2012). Routledge new developments in communication and society research. Routledge eBooks.
12.
Curran, James, et al.. (2011). Relation Guided Bootstrapping of Semantic Lexicons. Meeting of the Association for Computational Linguistics. 266–270.7 indexed citations
13.
Tse, Daniel & James Curran. (2010). Chinese CCGbank: extracting CCG derivations from the Penn Chinese Treebank. International Conference on Computational Linguistics. 1083–1091.18 indexed citations
14.
Honnibal, Matthew, James Curran, & Johan Bos. (2010). Rebanking CCGbank for Improved NP Interpretation. University of Groningen research database (University of Groningen / Centre for Information Technology). 207–215.13 indexed citations
15.
Honnibal, Matthew, et al.. (2010). SCHWA: PETE Using CCG Dependencies with the C&C Parser. Meeting of the Association for Computational Linguistics. 313–316.2 indexed citations
16.
Curran, James, et al.. (2008). Parsing Noun Phrase Structure with CCG. Meeting of the Association for Computational Linguistics. 335–343.13 indexed citations
17.
Bos, Johan, et al.. (2007). The Pronto QA system at TREC-2007: harvesting hyponyms, using nominalisation patterns, and computing answer cardinality. Text REtrieval Conference.6 indexed citations
18.
Clark, Stephen, Mark Steedman, & James Curran. (2004). Object-Extraction and Question-Parsing using CCG.. Edinburgh Research Explorer (University of Edinburgh). 111–118.29 indexed citations
19.
Mauch, T., Tara Murphy, H. Buttery, et al.. (2003). VizieR Online Data Catalog: Sydney University Molonglo Sky Survey (SUMSS V2.1) (Mauch+ 2008).1 indexed citations
20.
Leidner, Jochen L., Johan Bos, James Curran, et al.. (2003). QED: The Edinburgh TREC-2003 Question Answering System. Edinburgh Research Explorer. 631–635.6 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.