The field of ontology-based systems and process mining is witnessing significant developments, with a focus on improving the quality and effectiveness of these systems. Researchers are exploring new methods for evaluating the fitness of ontologies for specific tasks, such as question generation, and developing innovative tools and frameworks to support the design and analysis of complex systems. Notable papers in this area include: the proposal of a set of requirements and task-specific metrics for evaluating the fitness of ontologies for question generation tasks, the introduction of the eST$^2$ Miner, a process discovery algorithm that can directly handle partially ordered input, and the development of OnSET, a novel system that allows non-expert users to easily build queries with visual user guidance over knowledge graphs.
Advances in Ontology-Based Systems and Process Mining
Sources
Evaluating the Fitness of Ontologies for the Task of Question Generation
A Python toolkit for dealing with Petri nets over ontological graphs
Object Oriented-Based Metrics to Predict Fault Proneness in Software Design
eST$^2$ Miner -- Process Discovery Based on Firing Partial Orders
OnSET: Ontology and Semantic Exploration Toolkit
A Complete Formal Specification and Verification of the BESW software control system of the Maeslant Storm Surge Barrier
Constructing Witnesses for Lower Bounds on Behavioural Distances
A Phenomenological Approach to Analyzing User Queries in IT Systems Using Heidegger's Fundamental Ontology