This research project focuses on developing explainable AI solutions to decision support systems, by combining knowledge graphs, machine reasoning and machine learning. Knowledge graphs is a promising data and knowledge organisation, synthesis and management approach, and we have developed scalable reasoning tools for knowledge graphs coupled with ontological rules that describe domain knowledge or business rules. Therefore, this project aims to study the problem of incorporating such high-level knowledge and formal reasoning in the analysis of cross-media data (obtained from vision, sound, language and other sources). Moreover, such knowledge and reasoning can be integrated with machine learning models to provide powerful support for informed decision-making where a justification or explanation of the decision can potentially be retrieved.
Supervisors
