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.
Countries citing papers authored by Hamish Cunningham
Since
Specialization
Citations
This map shows the geographic impact of Hamish Cunningham'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 Hamish Cunningham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hamish Cunningham more than expected).
Fields of papers citing papers by Hamish Cunningham
This network shows the impact of papers produced by Hamish Cunningham. 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 Hamish Cunningham. The network helps show where Hamish Cunningham may publish in the future.
Co-authorship network of co-authors of Hamish Cunningham
This figure shows the co-authorship network connecting the top 25 collaborators of Hamish Cunningham.
A scholar is included among the top collaborators of Hamish Cunningham 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 Hamish Cunningham. Hamish Cunningham 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.
Tablan, Valentin, Kalina Bontcheva, Ian Roberts, Hamish Cunningham, & Marin Dimitrov. (2013). AnnoMarket: An Open Cloud Platform for NLP. Meeting of the Association for Computational Linguistics. 19–24.6 indexed citations
2.
Damljanović, Danica, et al.. (2010). Identification of the Question Focus: Combining Syntactic Analysis and Ontology-based Lookup through the User Interaction. Language Resources and Evaluation.14 indexed citations
3.
Li, Yaoyong, Kalina Bontcheva, & Hamish Cunningham. (2007). SVM Based Learning System for F-term Patent Classification. NTCIR.7 indexed citations
4.
Li, Yaoyong, Kalina Bontcheva, & Hamish Cunningham. (2007). Experiments of Opinion Analysis on the Corpora MPQA and NTCIR-6. NTCIR.9 indexed citations
5.
Tablan, Valentin, Wim Peters, Diana Maynard, & Hamish Cunningham. (2006). Creating Tools for Morphological Analysis of Sumerian. Language Resources and Evaluation. 1762–1765.6 indexed citations
6.
Tablan, Valentin, et al.. (2006). User-friendly ontology authoring using a controlled language. Language Resources and Evaluation. 35–40.15 indexed citations
7.
Li, Yaoyong, Kalina Bontcheva, & Hamish Cunningham. (2005). SVM Based Learning System For Information Extraction.13 indexed citations
8.
Paskaleva, Elena E., et al.. (2005). SLAVONIC NAMED ENTITIES IN GATE.2 indexed citations
9.
Maynard, Diana, Kalina Bontcheva, & Hamish Cunningham. (2004). Automatic Language-Independent Induction of Gazetteer Lists.. Language Resources and Evaluation.12 indexed citations
10.
Guthrie, Louise, Roberto Basili, Fabio Massimo Zanzotto, et al.. (2004). Large Scale Experiments for Semantic Labeling of Noun Phrases in Raw Text.. Language Resources and Evaluation.
11.
Reidsma, Dennis, Jan Kuper, Thierry Declerck, Horacio Saggion, & Hamish Cunningham. (2003). Cross document ontology based information for multimedia retrieval. University of Twente Research Information. 73–86.1 indexed citations
12.
Baker, Paul, Andrew Hardie, Tony McEnery, Hamish Cunningham, & Robert Gaizauskas. (2002). EMILLE, A 67-million word corpus of indic languages:Data collection, mark-up and harmonisation. Language Resources and Evaluation.39 indexed citations
13.
Pastra, Katerina, et al.. (2002). How feasible is the reuse of grammars for Named Entity Recognition. Language Resources and Evaluation.14 indexed citations
14.
Saggion, Horacio, et al.. (2002). Extracting Information for Automatic Indexing of Multimedia Material.. Language Resources and Evaluation.4 indexed citations
15.
Tablan, Valentin, Cristian Ursu, Kalina Bontcheva, et al.. (2002). A unicode-based environment for creation and use of language resources.. Language Resources and Evaluation.13 indexed citations
16.
Bontcheva, Kalina, Christopher Brewster, Fabio Ciravegna, et al.. (2001). Using HLT for Acquiring, Retrieving and Publishing Knowledge in AKT. Meeting of the Association for Computational Linguistics.2 indexed citations
17.
Bontcheva, Kalina, Hennie Brugman, Hamish Cunningham, Albert Russel, & Peter Wittenburg. (2000). An Experiment in Unifying Audio-Visual and Textual Infrastructures for Language Processing Research and Development. Max Planck Institute for Plasma Physics. 19–25.3 indexed citations
18.
Cunningham, Hamish, Diana Maynard, Kalina Bontcheva, Valentin Tablan, & Yorick Wilks. (2000). Experience using GATE for NLP R&D. International Conference on Computational Linguistics. 1–8.14 indexed citations
19.
Cunningham, Hamish, Kalina Bontcheva, Valentin Tablan, & Yorick Wilks. (2000). Software Infrastructure for Language Resources: a Taxonomy of Previous Work and a Requirements Analysis.. Language Resources and Evaluation.18 indexed citations
20.
Stevenson, Mark, Hamish Cunningham, & Yorick Wilks. (1998). Sense Tagging and Language Engineering.. European Conference on Artificial Intelligence. 185–189.4 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.