This map shows the geographic impact of James Cussens'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 Cussens with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Cussens more than expected).
This network shows the impact of papers produced by James Cussens. 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 Cussens. The network helps show where James Cussens may publish in the future.
Co-authorship network of co-authors of James Cussens
This figure shows the co-authorship network connecting the top 25 collaborators of James Cussens.
A scholar is included among the top collaborators of James Cussens 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 Cussens. James Cussens is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Studený, Milan, et al.. (2020). Dual Formulation of the Chordal Graph Conjecture. Explore Bristol Research. 449–460.1 indexed citations
6.
Cussens, James, et al.. (2020). Kernel-based Approach for Learning Causal Graphs from Mixed Data.. Bristol Research (University of Bristol). 221–232.1 indexed citations
7.
Cussens, James. (2020). GOBNILP: Learning Bayesian network structure with integer programming.. Bristol Research (University of Bristol). 605–608.1 indexed citations
Cussens, James, et al.. (2015). Learning failure-free PRISM programs. International Journal of Approximate Reasoning. 67. 73–110.1 indexed citations
13.
Cussens, James, et al.. (2013). Advances in Bayesian network learning using integer programming. Uncertainty in Artificial Intelligence. 182–191.46 indexed citations
14.
Hassan, Malik Tahir, Asim Karim, Suresh Manandhar, & James Cussens. (2009). Discriminative clustering for content-based tag recommendation in social bookmarking systems. Explore Bristol Research. 85–97.2 indexed citations
15.
Angelopoulos, Nicos & James Cussens. (2005). Exploiting informative priors for Bayesian classification and regression trees. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 641–646.7 indexed citations
Cussens, James, et al.. (2000). Incorporating linguistic structure into statistical language models - Discussion. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 358(1769).1 indexed citations
20.
Cussens, James, et al.. (2000). Experiments in Inductive Chart Parsing. Oxford University Research Archive (ORA) (University of Oxford).
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.