The Inkpot Natural Language Research Group is made up of faculty, staff, and students engaged in research about Computational Linguistics, Cognitive Rhetoric, and Computational Argumentation in various areas of application, including biomedical natural language processing, serious games, and persuasive technologies.
Inkpot developed out of the original HealthDoc Project (1994-2012) which developed Natural Language Generation systems to produce personalized health education materials. Inkpot's research methodology aims to combine knowledge-based and Machine Learning methods from Computational Linguistics to develop robust and reusable theories, methods, and software tools for Natural Language applications.
Inkpot is funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Social Sciences and Humanities Research Council of Canada (SSHRC).
We have been collaborating with Prof. Randy Harris (Department of English) and his students for the past several years on the development of a formal ontology of rhetorical figures and automated rhetorical annotation software tools. Ongoing work involves transfer of our informal database of rhetorical figuration to a relational database and a formal computational Semantic Web-based OWL (Web Ontology Language) ontology.
We are collaborating with Prof. Bob Mercer (Western University, Computer Science) and his students on the development of methods for mining information about argumentation structure from biomedical articles.
Mohammed Alliheedi (PhD). Thesis area: Mining argumentation structure in biomedical articles.
Omar Nafees (PhD) Thesis area: Computational analysis of relationships between rhetorical and argumentation structure in texts.
Jonathan Rodriguez (PhD). Topic area: Serious games.
George Ross (PhD, English). Topic area: Narrative in games.
Claus Strommer (PhD, 2011). Thesis title:
Pursuing the relations between saliency, context, intent, and
rhetorical figures in text media.
Jakub Gawryjolek (MMath, 1999). Thesis title: Automated
annotation and visualization of rhetorical figures.