This map shows the geographic impact of Paul Cook'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 Paul Cook with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Cook more than expected).
This network shows the impact of papers produced by Paul Cook. 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 Paul Cook. The network helps show where Paul Cook may publish in the future.
Co-authorship network of co-authors of Paul Cook
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Cook.
A scholar is included among the top collaborators of Paul Cook 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 Paul Cook. Paul Cook is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cook, Paul, et al.. (2020). Evaluating Sub-word Embeddings in Cross-lingual Models.. Language Resources and Evaluation. 2712–2719.2 indexed citations
8.
Cook, Paul, et al.. (2020). Joint Training for Learning Cross-lingual Embeddings with Sub-word Information without Parallel Corpora. Joint Conference on Lexical and Computational Semantics. 39–49.1 indexed citations
9.
Salehi, Bahar, Paul Cook, & Timothy Baldwin. (2016). Determining the Multiword Expression Inventory of a Surprise Language. International Conference on Computational Linguistics. 471–481.2 indexed citations
Cook, Paul, Jey Han Lau, Diana McCarthy, & Timothy Baldwin. (2014). Novel Word-sense Identification. International Conference on Computational Linguistics. 1624–1635.19 indexed citations
12.
Duong, Long, Paul Cook, Steven Bird, & Pavel Pecina. (2013). Simpler unsupervised POS tagging with bilingual projections. Meeting of the Association for Computational Linguistics. 634–639.14 indexed citations
13.
Lau, Jey Han, Paul Cook, & Timothy Baldwin. (2013). unimelb: Topic Modelling-based Word Sense Induction for Web Snippet Clustering. Joint Conference on Lexical and Computational Semantics. 2. 217–221.15 indexed citations
14.
Gella, Spandana, Bahar Salehi, Marco Lui, et al.. (2013). UniMelb_NLP-CORE: Integrating predictions from multiple domains and feature sets for estimating semantic textual similarity. Joint Conference on Lexical and Computational Semantics. 1. 207–215.3 indexed citations
15.
Cook, Paul & Graeme Hirst. (2013). Automatically Assessing Whether a Text Is Cliched, with Applications to Literary Analysis. North American Chapter of the Association for Computational Linguistics. 52–57.3 indexed citations
16.
Han, Bo, Paul Cook, & Timothy Baldwin. (2012). Automatically Constructing a Normalisation Dictionary for Microblogs. Empirical Methods in Natural Language Processing. 421–432.124 indexed citations
17.
Cook, Paul & Graeme Hirst. (2011). Automatic identification of words with novel but infrequent senses. Pacific Asia Conference on Language, Information, and Computation. 265–274.7 indexed citations
18.
Cook, Paul & Suzanne Stevenson. (2010). Automatically Identifying Changes in the Semantic Orientation of Words.. Language Resources and Evaluation.34 indexed citations
19.
Cook, Paul, et al.. (2008). Effects of telephone counseling on antipsychotic adherence and emergency department utilization.. PubMed. 14(12). 841–6.26 indexed citations
20.
Birrell, James R., et al.. (1998). Professional Development Schools and Teacher Educators' Beliefs: Challenges and Change.. Teacher education quarterly (Claremont, Calif.). 25(2). 63–80.10 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.