A parser for the efficient induction of biological grammars
(2005)
Presentation / Conference
Bryant, C., & Fredouille, D. (2005, August). A parser for the efficient induction of biological grammars. Presented at 15th International Conference on Inductive Logic Programming, Bonne, Germany
Dr Chris Bryant's Outputs (4)
Transforming general program proofs: a meta interpreter which expands negative literals (1997)
Presentation / Conference
West, M., Bryant, C., & McCluskey, T. (1997, July). Transforming general program proofs: a meta interpreter which expands negative literals. Presented at 7th International Workshop on Logic Program Synthesis and Transformation, Leuven, BelgiumThis paper provides a method for generating a proof tree from an instance and a general logic program viz one which includes negative literals. The method differs from previous work in the field in that negative literals are first unfolded and then... Read More about Transforming general program proofs: a meta interpreter which expands negative literals.
DataMariner, a commercially available data mining package, and its application to a chemistry domain (1995)
Presentation / Conference
Bryant, C., Adam, A., Taylor, D., Conroy, G., & Rowe, R. (1995, March). DataMariner, a commercially available data mining package, and its application to a chemistry domain. Presented at Data Mining, London, UK
Discovering knowledge hidden in a chemical database using a commercially available data mining tool (1995)
Presentation / Conference
Bryant, C., Adam, A., Taylor, D., Conroy, G., & Rowe, R. (1995, February). Discovering knowledge hidden in a chemical database using a commercially available data mining tool. Presented at IEE Colloquium on Knowledge Discovery in Databases, London, UKDescribes DataMariner, a commercially available tool that is designed to facilitate the discovery of knowledge hidden in databases. The potential of the tool for scientific applications is illustrated via a case study. This is both the first applicat... Read More about Discovering knowledge hidden in a chemical database using a commercially available data mining tool.