Dr Michael Stewart University of Western Australia

Dr Michael Stewart

Research Fellow

Theme 1


Perth - Hyatt Regency Perth, Perth, WA, Australia

The short text descriptions of maintenance work orders capture relationships between assets, their failure modes and the activities performed on those assets. Association rule mining is a pivotal knowledge discovery technique that automatically discovers these relationships by using machine learning to produce a list of association rules. However, inspecting these rules is a time-intensive and laborious task for domain experts, as not all rules are actually useful or interesting.

In this presentation Michael introduced QUARRY, a graph-based model that enables consumable and queryable insights from association rules. In contrast to existing systems, which take a list of rules and display them in a purpose-built visualisation, QUARRY enables association rules to be queried directly via graph queries, similarly to a knowledge graph. Michael demonstrates QUARRY on a sample dataset of maintenance work orders, illustrating the types of queries that can be performed over the association rules in order to provide useful insights into the data. https://ajcai2022.org/accepted-papers/

Presentation Link